医疗人工智能方向论文汇总思维导图

青简半卷

2023-08-24

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思维导图大纲

1.医学图像分割

1-1.医学图像分割

U-Net: Convolutional Networks for Biomedical Image Segmentation

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SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation

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Attention U-Net: Learning Where to Look for the Pancreas

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UNet++: A Nested U-Net Architecture for Medical Image Segmentation

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V-Net: Fully Convolutional Neural Networks for Volumetric Medical Image Segmentation

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Brain Tumor Segmentation with Deep Neural Networks

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UNet 3+: A Full-Scale Connected UNet for Medical Image Segmentation

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Recurrent Residual Convolutional Neural Network based on U-Net (R2U-Net) for Medical Image Segmentation

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UNet++: Redesigning Skip Connections to Exploit Multiscale Features in Image Segmentation

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UNETR: Transformers for 3D Medical Image Segmentation

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Automatic Brain Tumor Segmentation using Cascaded Anisotropic Convolutional Neural Networks

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Uncertainty-aware Self-ensembling Model for Semi-supervised 3D Left Atrium Segmentation

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ResUNet++: An Advanced Architecture for Medical Image Segmentation

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nnU-Net: Self-adapting Framework for U-Net-Based Medical Image Segmentation

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A Novel Focal Tversky loss function with improved Attention U-Net for lesion segmentation

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1-2.病灶分割

U-Net: Convolutional Networks for Biomedical Image Segmentation

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SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation

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Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation

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Pyramid Scene Parsing Network

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Skin Lesion Analysis Toward Melanoma Detection 2018: A Challenge Hosted by the International Skin Imaging Collaboration (ISIC)

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Skin Lesion Analysis Toward Melanoma Detection: A Challenge at the 2017 International Symposium on Biomedical Imaging (ISBI), Hosted by the International Skin Imaging Collaboration (ISIC)

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Road Extraction by Deep Residual U-Net

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Recurrent Residual Convolutional Neural Network based on U-Net (R2U-Net) for Medical Image Segmentation

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A Novel Focal Tversky loss function with improved Attention U-Net for lesion segmentation

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Boundary loss for highly unbalanced segmentation

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Automatic Liver and Tumor Segmentation of CT and MRI Volumes using Cascaded Fully Convolutional Neural Networks

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RECOD Titans at ISIC Challenge 2017

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Automatic Liver and Lesion Segmentation in CT Using Cascaded Fully Convolutional Neural Networks and 3D Conditional Random Fields

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One-shot domain adaptation in multiple sclerosis lesion segmentation using convolutional neural networks

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Acute and sub-acute stroke lesion segmentation from multimodal MRI

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1-3.脑肿瘤分割

Attention U-Net: Learning Where to Look for the Pancreas

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Brain Tumor Segmentation with Deep Neural Networks

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Automatic Brain Tumor Segmentation using Cascaded Anisotropic Convolutional Neural Networks

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Brain Tumor Segmentation and Radiomics Survival Prediction: Contribution to the BRATS 2017 Challenge

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3D MRI brain tumor segmentation using autoencoder regularization

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Autofocus Layer for Semantic Segmentation

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Association of genomic subtypes of lower-grade gliomas with shape features automatically extracted by a deep learning algorithm

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A Two-Stage Cascade Model with Variational Autoencoders and Attention Gates for MRI Brain Tumor Segmentation

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TBraTS: Trusted Brain Tumor Segmentation

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Efficient Multi-Scale 3D CNN with Fully Connected CRF for Accurate Brain Lesion Segmentation

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CNN-based Segmentation of Medical Imaging Data

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SegAN: Adversarial Network with Multi-scale $L_1$ Loss for Medical Image Segmentation

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Models Genesis: Generic Autodidactic Models for 3D Medical Image Analysis

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3D U-Net Based Brain Tumor Segmentation and Survival Days Prediction

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Learning Semantics-enriched Representation via Self-discovery, Self-classification, and Self-restoration

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1-4.大脑分割

Concurrent Spatial and Channel Squeeze & Excitation in Fully Convolutional Networks

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QuickNAT: A Fully Convolutional Network for Quick and Accurate Segmentation of Neuroanatomy

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MRI Super-Resolution using Multi-Channel Total Variation

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VoxResNet: Deep Voxelwise Residual Networks for Volumetric Brain Segmentation

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3D fully convolutional networks for subcortical segmentation in MRI: A large-scale study

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HyperDense-Net: A hyper-densely connected CNN for multi-modal image segmentation

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Association of genomic subtypes of lower-grade gliomas with shape features automatically extracted by a deep learning algorithm

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A Learning Strategy for Contrast-agnostic MRI Segmentation

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CrossMoDA 2021 challenge: Benchmark of Cross-Modality Domain Adaptation techniques for Vestibular Schwannoma and Cochlea Segmentation

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Deep Neural Networks for Anatomical Brain Segmentation

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Spatially Localized Atlas Network Tiles Enables 3D Whole Brain Segmentation from Limited Data

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Bayesian QuickNAT: Model Uncertainty in Deep Whole-Brain Segmentation for Structure-wise Quality Control

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3D Whole Brain Segmentation using Spatially Localized Atlas Network Tiles

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Project & Excite' Modules for Segmentation of Volumetric Medical Scans

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Importance Driven Continual Learning for Segmentation Across Domains

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1-5.细胞分割

U-Net: Convolutional Networks for Biomedical Image Segmentation

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Deep Learning in Single-Cell Analysis

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CE-Net: Context Encoder Network for 2D Medical Image Segmentation

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DoubleU-Net: A Deep Convolutional Neural Network for Medical Image Segmentation

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Fully Unsupervised Diversity Denoising with Convolutional Variational Autoencoders

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Applying Faster R-CNN for Object Detection on Malaria Images

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Cell Detection with Star-convex Polygons

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Scribble2Label: Scribble-Supervised Cell Segmentation via Self-Generating Pseudo-Labels with Consistency

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Automatic Label Correction for the Accurate Edge Detection of Overlapping Cervical Cells

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Microscopy Cell Segmentation via Adversarial Neural Networks

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Microscopy Cell Segmentation via Convolutional LSTM Networks

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Comparison-Based Convolutional Neural Networks for Cervical Cell/Clumps Detection in the Limited Data Scenario

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Accurate 3D Cell Segmentation using Deep Feature and CRF Refinement

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Multi-scale Cell Instance Segmentation with Keypoint Graph based Bounding Boxes

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DISCo: Deep learning, Instance Segmentation, and Correlations for cell segmentation in calcium imaging

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1-6.皮损分割

A Novel Focal Tversky loss function with improved Attention U-Net for lesion segmentation

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RECOD Titans at ISIC Challenge 2017

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Bi-Directional ConvLSTM U-Net with Densley Connected Convolutions

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Automatic skin lesion segmentation on dermoscopic images by the means of superpixel merging

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CA-Net: Comprehensive Attention Convolutional Neural Networks for Explainable Medical Image Segmentation

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MFSNet: A Multi Focus Segmentation Network for Skin Lesion Segmentation

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Automatic skin lesion segmentation with fully convolutional-deconvolutional networks

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Dense Pooling layers in Fully Convolutional Network for Skin Lesion Segmentation

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Deeply Supervised Rotation Equivariant Network for Lesion Segmentation in Dermoscopy Images

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Automatic Skin Lesion Segmentation Using Deep Fully Convolutional Networks

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Automatic Skin Lesion Segmentation Using GrabCut in HSV Colour Space

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Transformation Consistent Self-ensembling Model for Semi-supervised Medical Image Segmentation

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A Kernelized Manifold Mapping to Diminish the Effect of Adversarial Perturbations

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A Mutual Bootstrapping Model for Automated Skin Lesion Segmentation and Classification

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Handling Inter-Annotator Agreement for Automated Skin Lesion Segmentation

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1-7.视网膜血管分割

U-Net: Convolutional Networks for Biomedical Image Segmentation

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Road Extraction by Deep Residual U-Net

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Recurrent Residual Convolutional Neural Network based on U-Net (R2U-Net) for Medical Image Segmentation

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Dynamic Deep Networks for Retinal Vessel Segmentation

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LadderNet: Multi-path networks based on U-Net for medical image segmentation

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Retinal Vessel Segmentation in Fundoscopic Images with Generative Adversarial Networks

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Accurate Retinal Vessel Segmentation via Octave Convolution Neural Network

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Retinal Vessel Segmentation based on Fully Convolutional Networks

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IterNet: Retinal Image Segmentation Utilizing Structural Redundancy in Vessel Networks

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Channel Attention Residual U-Net for Retinal Vessel Segmentation

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SA-UNet: Spatial Attention U-Net for Retinal Vessel Segmentation

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RV-GAN: Segmenting Retinal Vascular Structure in Fundus Photographs using a Novel Multi-scale Generative Adversarial Network

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Learning to Address Intra-segment Misclassification in Retinal Imaging

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Retinal Image Restoration and Vessel Segmentation using Modified Cycle-CBAM and CBAM-UNet

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007: Democratically Finding The Cause of Packet Drops

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1-8.MRI分割

Acute and sub-acute stroke lesion segmentation from multimodal MRI

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A Learning Strategy for Contrast-agnostic MRI Segmentation

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Anatomical Priors in Convolutional Networks for Unsupervised Biomedical Segmentation

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The International Workshop on Osteoarthritis Imaging Knee MRI Segmentation Challenge: A Multi-Institute Evaluation and Analysis Framework on a Standardized Dataset

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Label-set Loss Functions for Partial Supervision: Application to Fetal Brain 3D MRI Parcellation

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3D Densely Convolutional Networks for Volumetric Segmentation

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3D Densely Convolutional Networks for VolumetricSegmentation

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Isointense Infant Brain Segmentation with a Hyper-dense Connected Convolutional Neural Network

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Deep CNN ensembles and suggestive annotations for infant brain MRI segmentation

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Unsupervised Deep Learning for Bayesian Brain MRI Segmentation

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Cardiac MRI Segmentation with Strong Anatomical Guarantees

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Improving Robustness of Deep Learning Based Knee MRI Segmentation: Mixup and Adversarial Domain Adaptation

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Distributionally Robust Deep Learning using Hardness Weighted Sampling

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Shape-aware Meta-learning for Generalizing Prostate MRI Segmentation to Unseen Domains

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PSIGAN: Joint probabilistic segmentation and image distribution matching for unpaired cross-modality adaptation based MRI segmentation

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1-9.3D医学影像分割

1.BreastScreening: On the Use of Multi-Modality in Medical Imaging Diagnosis

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2.UNETR: Transformers for 3D Medical Image Segmentation

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3.On the Compactness, Efficiency, and Representation of 3D Convolutional Networks: Brain Parcellation as a Pretext Task

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4.Med3D: Transfer Learning for 3D Medical Image Analysis

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5.3D fully convolutional networks for subcortical segmentation in MRI: A large-scale study

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6.Association of genomic subtypes of lower-grade gliomas with shape features automatically extracted by a deep learning algorithm

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7.Enforcing temporal consistency in Deep Learning segmentation of brain MR images

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8.Efficient Multi-Scale 3D CNN with Fully Connected CRF for Accurate Brain Lesion Segmentation

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9.Conditional Random Fields as Recurrent Neural Networks for 3D Medical Imaging Segmentation

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10.AnatomyNet: Deep Learning for Fast and Fully Automated Whole-volume Segmentation of Head and Neck Anatomy

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11.Elastic Boundary Projection for 3D Medical Image Segmentation

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12.Semantic Context Forests for Learning-Based Knee Cartilage Segmentation in 3D MR Images

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13.Combining Fully Convolutional and Recurrent Neural Networks for 3D Biomedical Image Segmentation

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14.3D Densely Convolutional Networks for VolumetricSegmentation

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15.TernaryNet: Faster Deep Model Inference without GPUs for Medical 3D Segmentation using Sparse and Binary Convolutions

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1-10.心脏分割

1.TransUNet: Transformers Make Strong Encoders for Medical Image Segmentation

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2.Swin-Unet: Unet-like Pure Transformer for Medical Image Segmentation

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3.A Fully Convolutional Neural Network for Cardiac Segmentation in Short-Axis MRI

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4.Self-Supervision with Superpixels: Training Few-shot Medical Image Segmentation without Annotation

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5.PnP-AdaNet: Plug-and-Play Adversarial Domain Adaptation Network with a Benchmark at Cross-modality Cardiac Segmentation

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6.Disentangle, align and fuse for multimodal and semi-supervised image segmentation

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7.Efficient Model Monitoring for Quality Control in Cardiac Image Segmentation

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8.3D Consistent & Robust Segmentation of Cardiac Images by Deep Learning with Spatial Propagation

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9.Joint Learning of Motion Estimation and Segmentation for Cardiac MR Image Sequences

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10.Explainable cardiac pathology classification on cine MRI with motion characterization by semi-supervised learning of apparent flow

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11.Cardiac MRI Segmentation with Strong Anatomical Guarantees

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12.An Automatic Cardiac Segmentation Framework based on Multi-sequence MR Image

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13.L-CO-Net: Learned Condensation-Optimization Network for Clinical Parameter Estimation from Cardiac Cine MRI

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14.Cardiac Segmentation with Strong Anatomical Guarantees

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15.Learning Directional Feature Maps for Cardiac MRI Segmentation

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1-11.肝脏分割

1.The Liver Tumor Segmentation Benchmark (LiTS)

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2.Med3D: Transfer Learning for 3D Medical Image Analysis

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3.Models Genesis: Generic Autodidactic Models for 3D Medical Image Analysis

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4.Learning Semantics-enriched Representation via Self-discovery, Self-classification, and Self-restoration

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5.H-DenseUNet: Hybrid Densely Connected UNet for Liver and Tumor Segmentation from CT Volumes

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6.Imperfect Segmentation Labels: How Much Do They Matter?

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7.Transformation Consistent Self-ensembling Model for Semi-supervised Medical Image Segmentation

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8.Liver Lesion Segmentation with slice-wise 2D Tiramisu and Tversky loss function

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9.Fully Automatic Liver Attenuation Estimation Combing CNN Segmentation and Morphological Operations

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10.Generating large labeled data sets for laparoscopic image processing tasks using unpaired image-to-image translation

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11.Optimal input configuration of dynamic contrast enhanced MRI in convolutional neural networks for liver segmentation

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12.Liver segmentation and metastases detection in MR images using convolutional neural networks

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13.KiU-Net: Overcomplete Convolutional Architectures for Biomedical Image and Volumetric Segmentation

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14.Upgraded W-Net with Attention Gates and its Application in Unsupervised 3D Liver Segmentation

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15.Automatic Liver Segmentation from CT Images Using Deep Learning Algorithms: A Comparative Study

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1-12.半监督医学图像分割

1.Mutual Consistency Learning for Semi-supervised Medical Image Segmentation

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2.MisMatch: Calibrated Segmentation via Consistency on Differential Morphological Feature Perturbations with Limited Labels

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3.Exploring Smoothness and Class-Separation for Semi-supervised Medical Image Segmentation

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4.When CNN Meet with ViT: Towards Semi-Supervised Learning for Multi-Class Medical Image Semantic Segmentation

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5.Transformation Consistent Self-ensembling Model for Semi-supervised Medical Image Segmentation

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6.A generic ensemble based deep convolutional neural network for semi-supervised medical image segmentation

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7.Semi-supervised Medical Image Segmentation through Dual-task Consistency

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8.A Teacher-Student Framework for Semi-supervised Medical Image Segmentation From Mixed Supervision

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9.Dual-Task Mutual Learning for Semi-Supervised Medical Image Segmentation

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10.Self-Paced Contrastive Learning for Semi-supervised Medical Image Segmentation with Meta-labels

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11.Duo-SegNet: Adversarial Dual-Views for Semi-Supervised Medical Image Segmentation

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12.All-Around Real Label Supervision: Cyclic Prototype Consistency Learning for Semi-supervised Medical Image Segmentation

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13.Inconsistency-aware Uncertainty Estimation for Semi-supervised Medical Image Segmentation

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14.Semi-Supervised Medical Image Segmentation via Cross Teaching between CNN and Transformer

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15.An Embarrassingly Simple Consistency Regularization Method for Semi-Supervised Medical Image Segmentation

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1-13.大脑图像分割

1.FusionNet: A deep fully residual convolutional neural network for image segmentation in connectomics

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2.Non-local U-Net for Biomedical Image Segmentation

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3.Enforcing temporal consistency in Deep Learning segmentation of brain MR images

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4.NeuroNet: Fast and Robust Reproduction of Multiple Brain Image Segmentation Pipelines

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5.Few-shot 3D Multi-modal Medical Image Segmentation using Generative Adversarial Learning

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6.Unsupervised Deep Learning for Bayesian Brain MRI Segmentation

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7.ROAM: Random Layer Mixup for Semi-Supervised Learning in Medical Imaging

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8.Using deep convolutional neural networks for neonatal brain image segmentation

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9.A Contrast-Adaptive Method for Simultaneous Whole-Brain and Lesion Segmentation in Multiple Sclerosis

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10.A Longitudinal Method for Simultaneous Whole-Brain and Lesion Segmentation in Multiple Sclerosis

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11.DAM-AL: Dilated Attention Mechanism with Attention Loss for 3D Infant Brain Image Segmentation

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12.An Open-Source Tool for Longitudinal Whole-Brain and White Matter Lesion Segmentation

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13.Subject-Specific Lesion Generation and Pseudo-Healthy Synthesis for Multiple Sclerosis Brain Images

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14.Learning from imperfect training data using a robust loss function: application to brain image segmentation

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1-14.虹膜分割

1.Reconstruction and Quantification of 3D Iris Surface for Angle-Closure Glaucoma Detection in Anterior Segment OCT

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2.Open Source Iris Recognition Hardware and Software with Presentation Attack Detection

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3.Iris Recognition with Image Segmentation Employing Retrained Off-the-Shelf Deep Neural Networks

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4.Learning-Free Iris Segmentation Revisited: A First Step Toward Fast Volumetric Operation Over Video Samples

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5.Post-mortem Iris Recognition with Deep-Learning-based Image Segmentation

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6.Joint Iris Segmentation and Localization Using Deep Multi-task Learning Framework

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7.Gender Classification from Iris Texture Images Using a New Set of Binary Statistical Image Features

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8.A Resource-Efficient Embedded Iris Recognition System Using Fully Convolutional Networks

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9.Boltzmann Exploration Expectation–Maximisation

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10.Interpretable Deep Learning-Based Forensic Iris Segmentation and Recognition

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11.KartalOl: Transfer learning using deep neural network for iris segmentation and localization: New dataset for iris segmentation

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12.Saliency-Guided Textured Contact Lens-Aware Iris Recognition

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13.Artificial Pupil Dilation for Data Augmentation in Iris Semantic Segmentation

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1-15.体积医学图像分割

1.V-Net: Fully Convolutional Neural Networks for Volumetric Medical Image Segmentation

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2.On the Compactness, Efficiency, and Representation of 3D Convolutional Networks: Brain Parcellation as a Pretext Task

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3.Conditional Random Fields as Recurrent Neural Networks for 3D Medical Imaging Segmentation

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4.nnFormer: Interleaved Transformer for Volumetric Segmentation

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5.3D Densely Convolutional Networks for VolumetricSegmentation

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6.KiU-Net: Overcomplete Convolutional Architectures for Biomedical Image and Volumetric Segmentation

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7.Positional Contrastive Learning for Volumetric Medical Image Segmentation

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8.A Robust Volumetric Transformer for Accurate 3D Tumor Segmentation

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9.Memory-efficient Segmentation of High-resolution Volumetric MicroCT Images

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10.Med-DANet: Dynamic Architecture Network for Efficient Medical Volumetric Segmentation

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11.Rethinking Bayesian Deep Learning Methods for Semi-Supervised Volumetric Medical Image Segmentation

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12.AdaWAC: Adaptively Weighted Augmentation Consistency Regularization for Volumetric Medical Image Segmentation

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1-16.胰腺分割

1.U-Net: Convolutional Networks for Biomedical Image Segmentation

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2.Attention U-Net: Learning Where to Look for the Pancreas

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3.A Fixed-Point Model for Pancreas Segmentation in Abdominal CT Scans

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4.Recurrent Saliency Transformation Network: Incorporating Multi-Stage Visual Cues for Small Organ Segmentation

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5.U-Net Fixed-Point Quantization for Medical Image Segmentation

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6.TernaryNet: Faster Deep Model Inference without GPUs for Medical 3D Segmentation using Sparse and Binary Convolutions

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7.AbdomenCT-1K: Is Abdominal Organ Segmentation A Solved Problem?

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8.Inter-slice Context Residual Learning for 3D Medical Image Segmentation

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9.Uncertainty-Based Dynamic Graph Neighborhoods For Medical Segmentation

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10.Hierarchical 3D Feature Learning for Pancreas Segmentation

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11.Dynamic Linear Transformer for 3D Biomedical Image Segmentation

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12.Unsupervised Domain Adaptation through Shape Modeling for Medical Image Segmentation

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1-17.视频息肉分割

1.U-Net: Convolutional Networks for Biomedical Image Segmentation

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2.UNet++: A Nested U-Net Architecture for Medical Image Segmentation

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3.PraNet: Parallel Reverse Attention Network for Polyp Segmentation

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4.Video Polyp Segmentation: A Deep Learning Perspective

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5.Progressively Normalized Self-Attention Network for Video Polyp Segmentation

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6.See More, Know More: Unsupervised Video Object Segmentation with Co-Attention Siamese Networks

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7.MATNet: Motion-Attentive Transition Network for Zero-Shot Video Object Segmentation

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8.Dynamic Context-Sensitive Filtering Network for Video Salient Object Detection

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9.Shallow Attention Network for Polyp Segmentation

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10.Full-Duplex Strategy for Video Object Segmentation

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11.The Emergence of Objectness: Learning Zero-Shot Segmentation from Videos

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1-18.肺结节分割

1.Road Extraction by Deep Residual U-Net

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2.Recurrent Residual Convolutional Neural Network based on U-Net (R2U-Net) for Medical Image Segmentation

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3.Bi-Directional ConvLSTM U-Net with Densley Connected Convolutions

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4.Models Genesis: Generic Autodidactic Models for 3D Medical Image Analysis

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5.Learning Semantics-enriched Representation via Self-discovery, Self-classification, and Self-restoration

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6.iW-Net: an automatic and minimalistic interactive lung nodule segmentation deep network

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7.Level set image segmentation with velocity term learned from data with applications to lung nodule segmentation

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8.U-Det: A Modified U-Net architecture with bidirectional feature network for lung nodule segmentation

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1-19.皮肤癌分割

1.U-Net: Convolutional Networks for Biomedical Image Segmentation

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2.Road Extraction by Deep Residual U-Net

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3.Recurrent Residual Convolutional Neural Network based on U-Net (R2U-Net) for Medical Image Segmentation

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4.DoubleU-Net: A Deep Convolutional Neural Network for Medical Image Segmentation

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5.FocusNet: An attention-based Fully Convolutional Network for Medical Image Segmentation

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6.Skin Cancer Segmentation and Classification with NABLA-N and Inception Recurrent Residual Convolutional Networks

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7.Skin Lesion Segmentation using SegNet with Binary Cross-Entropy

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8.Training on Polar Image Transformations Improves Biomedical Image Segmentation

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2.脑电图

2-1.脑电图

1.SGDR: Stochastic Gradient Descent with Warm Restarts

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2.Learning Representations from EEG with Deep Recurrent-Convolutional Neural Networks

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3.EEGNet: A Compact Convolutional Network for EEG-based Brain-Computer Interfaces

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4.DeepSleepNet: a Model for Automatic Sleep Stage Scoring based on Raw Single-Channel EEG

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5.Deep learning with convolutional neural networks for EEG decoding and visualization

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6.U-Time: A Fully Convolutional Network for Time Series Segmentation Applied to Sleep Staging

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code

7.An IoT Endpoint System-on-Chip for Secure and Energy-Efficient Near-Sensor Analytics

论文

code

8.Comparative evaluation of state-of-the-art algorithms for SSVEP-based BCIs

论文

code

9.Robustifying Independent Component Analysis by Adjusting for Group-Wise Stationary Noise

论文

code

10.Deep learning-based electroencephalography analysis: a systematic review

论文

code

11.SleepEEGNet: Automated Sleep Stage Scoring with Sequence to Sequence Deep Learning Approach

论文

code

12.SeizureNet: Multi-Spectral Deep Feature Learning for Seizure Type Classification

论文

code

13.Advancing NLP with Cognitive Language Processing Signals

论文

code

14.An Open-source Toolbox for Analysing and Processing PhysioNet Databases in MATLAB and Octave

论文

code

15.Using Riemannian geometry for SSVEP-based Brain Computer Interface

论文

code

2-2.脑电解码

1.Deep learning with convolutional neural networks for EEG decoding and visualization

论文

code

2.Transformer-based Spatial-Temporal Feature Learning for EEG Decoding

论文

code

3.Decoding P300 Variability using Convolutional Neural Networks

论文

code

4.Subject-Aware Contrastive Learning for Biosignals

论文

code

5.Decoding kinetic features of hand motor preparation from single‐trial EEG using convolutional neural networks

论文

code

6.Uncertainty Detection and Reduction in Neural Decoding of EEG Signals

论文

code

7.ExBrainable: An Open-Source GUI for CNN-based EEG Decoding and Model Interpretation

论文

code

8.Physics-inform attention temporal convolutional network for EEG-based motor imagery classification

论文

code

9.MAtt: A Manifold Attention Network for EEG Decoding

论文

code

10.fMRI from EEG is only Deep Learning away: the use of interpretable DL to unravel EEG-fMRI relationships

论文

code

11.Enhancing Low-Density EEG-Based Brain-Computer Interfaces with Similarity-Keeping Knowledge Distillation

论文

code

2-3.脑电去噪

1.EEGdenoiseNet: A benchmark dataset for end-to-end deep learning solutions of EEG denoising

论文

code

2.Improved robust weighted averaging for event-related potentials in EEG

论文

code

3.Embedding Decomposition for Artifacts Removal in EEG Signals

论文

code

3.药物发现

3-1.药物发现

1.Semi-Supervised Classification with Graph Convolutional Networks

论文

code

2.Neural Message Passing for Quantum Chemistry

论文

code

3.Gated Graph Sequence Neural Networks

论文

code

4.Junction Tree Variational Autoencoder for Molecular Graph Generation

论文

code

5.Self-Normalizing Neural Networks

论文

code

6.Convolutional Networks on Graphs for Learning Molecular Fingerprints

论文

code

7.PhysNet: A Neural Network for Predicting Energies, Forces, Dipole Moments and Partial Charges

论文

code

8.Generating Focussed Molecule Libraries for Drug Discovery with Recurrent Neural Networks

论文

code

9.Molecule Attention Transformer

论文

code

10.Directional Message Passing for Molecular Graphs

论文

code

11.An Overview of Multi-Task Learning in Deep Neural Networks

论文

code

12.DeepDTA: Deep Drug-Target Binding Affinity Prediction

论文

code

13.Spatial Graph Attention and Curiosity-driven Policy for Antiviral Drug Discovery

论文

code

14.Atomic Convolutional Networks for Predicting Protein-Ligand Binding Affinity

论文

code

15.ChemGAN challenge for drug discovery: can AI reproduce natural chemical diversity? 28 Aug 2017 · Mostapha Benhenda · Edit social preview

论文

code

3-2.药物反应预测

1.Variational Autoencoder for Anti-Cancer Drug Response Prediction

论文

code

2.Learning Curves for Drug Response Prediction in Cancer Cell Lines

论文

code

3.ASGARD: A Single-cell Guided pipeline to Aid Repurposing of Drugs

论文

code

4.Data augmentation and multimodal learning for predicting drug response in patient-derived xenografts from gene expressions and histology images

论文

code

5.A Fair Experimental Comparison of Neural Network Architectures for Latent Representations of Multi-Omics for Drug Response Prediction

论文

code

6.Prediction of drug effectiveness in rheumatoid arthritis patients based on machine learning algorithms

论文

code

7.TransEDRP: Dual Transformer model with Edge Emdedded for Drug Respond Prediction

论文

code

4.心电图（ECG）

4-1.死亡率预测

1.Multitask learning and benchmarking with clinical time series data

论文

code

2.Efficient nonparametric statistical inference on population feature importance using Shapley values

论文

code

3.MIMIC-III, a freely accessible critical care database

论文

code

4.Interpretable Outcome Prediction with Sparse Bayesian Neural Networks in Intensive Care

论文

code

5.Using Clinical Notes with Time Series Data for ICU Management

论文

code

6.Benchmarking machine learning models on multi-centre eICU critical care dataset

论文

code

7.Neural Document Embeddings for Intensive Care Patient Mortality Prediction

论文

code

8.Benchmark of Deep Learning Models on Large Healthcare MIMIC Datasets

论文

code

9.Early hospital mortality prediction using vital signals

论文

code

10.Countdown Regression: Sharp and Calibrated Survival Predictions

论文

code

11.Interpretable Patient Mortality Prediction with Multi-value Rule Sets

论文

code

12.Dynamic Measurement Scheduling for Event Forecasting using Deep RL

论文

code

13.Knowledge-based Analysis for Mortality Prediction from CT Images

论文

code

14.Analysis | OPEN | Published: 17 June 2019 Multitask learning and benchmarking with clinical time series data

论文

code

15.Evaluation of Embeddings of Laboratory Test Codes for Patients at a Cancer Center

论文

code

4-2.心电图分类

1.Deep Learning for ECG Classification

论文

code

2.Towards understanding ECG rhythm classification using convolutional neural networks and attention mappings

论文

code

3.Anomaly Detection in Time Series with Triadic Motif Fields and Application in Atrial Fibrillation ECG Classification

论文

code

4.Voice2Series: Reprogramming Acoustic Models for Time Series Classification

论文

code

5.ENCASE: An ENsemble ClASsifiEr for ECG classification using expert features and deep neural networks

论文

code

6.A Comparison of 1-D and 2-D Deep Convolutional Neural Networks in ECG Classification

论文

code

7.Automatic diagnosis of the 12-lead ECG using a deep neural network

论文

code

8.Diffeomorphic Temporal Alignment Nets

论文

code

9.Enhance CNN Robustness Against Noises for Classification of 12-Lead ECG with Variable Length

论文

code

10.ECG beats classification via online sparse dictionary and time pyramid matching

论文

code

11.Atrial Fibrillation Detection and ECG Classification based on CNN-BiLSTM

论文

code

12.Classification of 12-lead ECGs: the PhysioNet/ Computing in Cardiology Challenge 2020

论文

code

13.Convolutional Neural Network and Rule-Based Algorithms for Classifying 12-lead ECGs

论文

code

14.Self-supervised representation learning from 12-lead ECG data

论文

code

15.A practical system based on CNN-BLSTM network for accurate classification of ECG heartbeats of MIT-BIH imbalanced dataset

论文

code

4-3.心电图（ECG）

1.ECG Heartbeat Classification: A Deep Transferable Representation

论文

code

2.ECG arrhythmia classification using a 2-D convolutional neural network

论文

code

3.Cardiologist-Level Arrhythmia Detection with Convolutional Neural Networks

论文

code

4.An Open-source Toolbox for Analysing and Processing PhysioNet Databases in MATLAB and Octave

论文

code

5.Deep Learning for ECG Classification

论文

code

6.Long-term Blood Pressure Prediction with Deep Recurrent Neural Networks

论文

code

7.Towards understanding ECG rhythm classification using convolutional neural networks and attention mappings

论文

code

8.Anomaly Detection in Time Series with Triadic Motif Fields and Application in Atrial Fibrillation ECG Classification

论文

code

9.Blind ECG Restoration by Operational Cycle-GANs

论文

code

10.Comparing feature-based classifiers and convolutional neural networks to detect arrhythmia from short segments of ECG

论文

code

11.Real time P, QRS and T wave detection by QRS matched filter method

论文

code

12.VFPred: A Fusion of Signal Processing and Machine Learning techniques in Detecting Ventricular Fibrillation from ECG Signals

论文

code

13.Arrhythmia Detection Using Deep Convolutional Neural Network With Long Duration ECG Signals

论文

code

14.A Comparison of 1-D and 2-D Deep Convolutional Neural Networks in ECG Classification

论文

code

15.ECG Segmentation by Neural Networks: Errors and Correction

论文

code

4-4.心率失常检测

1.ECG Heartbeat Classification: A Deep Transferable Representation

论文

code

2.ECG arrhythmia classification using a 2-D convolutional neural network

论文

code

3.Cardiologist-Level Arrhythmia Detection with Convolutional Neural Networks

论文

code

4.Inter- and intra- patient ECG heartbeat classification for arrhythmia detection: a sequence to sequence deep learning approach

论文

code

5.An Open-source Toolbox for Analysing and Processing PhysioNet Databases in MATLAB and Octave

论文

code

6.Towards understanding ECG rhythm classification using convolutional neural networks and attention mappings

论文

code

7.Comparing feature-based classifiers and convolutional neural networks to detect arrhythmia from short segments of ECG

论文

code

8.ENCASE: An ENsemble ClASsifiEr for ECG classification using expert features and deep neural networks

论文

code

9.VFPred: A Fusion of Signal Processing and Machine Learning techniques in Detecting Ventricular Fibrillation from ECG Signals

论文

code

10.Arrhythmia Detection Using Deep Convolutional Neural Network With Long Duration ECG Signals

论文

code

11.Detection and Classification of Cardiac Arrhythmias by a Challenge-Best Deep Learning Neural Network Model

论文

code

12.ECG-TCN: Wearable Cardiac Arrhythmia Detection with a Temporal Convolutional Network

论文

code

13.ECG-Based Heart Arrhythmia Diagnosis Through Attentional Convolutional Neural Networks

论文

code

14.ECG-ATK-GAN: Robustness against Adversarial Attacks on ECGs using Conditional Generative Adversarial Networks

论文

code

15.End-to-End Optimized Arrhythmia Detection Pipeline using Machine Learning for Ultra-Edge Devices

论文

code

4-5.心率变异性

1.Real-Time Monitoring of User Stress, Heart Rate and Heart Rate Variability on Mobile Devices

论文

code

2.Remote Photoplethysmograph Signal Measurement from Facial Videos Using Spatio-Temporal Networks

论文

code

3.SCAMPS: Synthetics for Camera Measurement of Physiological Signals

论文

code

4.Specific Differential Entropy Rate Estimation for Continuous-Valued Time Series

论文

code

5.Sleep quality prediction in caregivers using physiological signals

论文

code

6.A persistent homology approach to heart rate variability analysis with an application to sleep-wake classification

论文

code

7.RPnet: A Deep Learning approach for robust R Peak detection in noisy ECG

论文

code

8.Video-based Remote Physiological Measurement via Cross-verified Feature Disentangling

论文

code

9.Inter-Beat Interval Estimation with Tiramisu Model: A Novel Approach with Reduced Error

论文

code

10.PhysioMTL: Personalizing Physiological Patterns using Optimal Transport Multi-Task Regression

论文

code

11.Video-based Remote Physiological Measurement via Self-supervised Learning

论文

code

12.Pan-Tompkins++: A Robust Approach to Detect R-peaks in ECG Signals

论文

code

13.CardiacGen: A Hierarchical Deep Generative Model for Cardiac Signals

论文

code

4-6.心跳分类

1.ECG Heartbeat Classification: A Deep Transferable Representation

论文

code

2.Inter- and intra- patient ECG heartbeat classification for arrhythmia detection: a sequence to sequence deep learning approach

论文

code

3.Heartbeat classification fusing temporal and morphological information of ECGs via ensemble of classifiers

论文

code

4.Construe: a software solution for the explanation-based interpretation of time series

论文

code

5.ATCN: Resource-Efficient Processing of Time Series on Edge

论文

code

6.ECG Heartbeat Classification Using Multimodal Fusion

论文

code

4-7.心电图去噪

1.Blind ECG Restoration by Operational Cycle-GANs

论文

code

2.Hierarchical Filtering with Online Learned Priors for ECG Denoising

论文

code

4-8.心肌梗塞检测

1.ECG Heartbeat Classification: A Deep Transferable Representation

论文

code

2.Deep Learning for Cardiologist-level Myocardial Infarction Detection in Electrocardiograms

论文

code

5.医学诊断

5-1.医学诊断

1.BreastScreening: On the Use of Multi-Modality in Medical Imaging Diagnosis

论文

code

2.Maximum Likelihood with Bias-Corrected Calibration is Hard-To-Beat at Label Shift Adaptation

论文

code

3.DropConnect Is Effective in Modeling Uncertainty of Bayesian Deep Networks

论文

code

4.A Benchmark of Medical Out of Distribution Detection

论文

code

5.Multi-layer Representation Learning for Medical Concepts

论文

code

6.High-Resolution Breast Cancer Screening with Multi-View Deep Convolutional Neural Networks

论文

code

7.TCAV: Relative concept importance testing with Linear Concept Activation Vectors

论文

code

8.Deep Neural Networks Improve Radiologists' Performance in Breast Cancer Screening

论文

code

9.D-UNet: a dimension-fusion U shape network for chronic stroke lesion segmentation

论文

code

10.UnMask: Adversarial Detection and Defense Through Robust Feature Alignment

论文

code

11.Automated Model Design and Benchmarking of 3D Deep Learning Models for COVID-19 Detection with Chest CT Scans

论文

code

12.SKID: Self-Supervised Learning for Knee Injury Diagnosis from MRI Data

论文

code

13.Patient Embeddings in Healthcare and Insurance Applications

论文

code

14.RuMedBench: A Russian Medical Language Understanding Benchmark

论文

code

15.Reasoning with Language Model Prompting: A Survey

论文

code

5-2.视网膜OCT疾病分类

1.Deep Residual Learning for Image Recognition

论文

code

2.MobileNetV2: Inverted Residuals and Linear Bottlenecks

论文

code

3.Rethinking the Inception Architecture for Computer Vision

论文

4.Xception: Deep Learning With Depthwise Separable Convolutions

论文

code

5.Optic-Net: A Novel Convolutional Neural Network for Diagnosis of Retinal Diseases from Optical Tomography Images

论文

code

6.Retinal OCT disease classification with variational autoencoder regularization

论文

code

7.Improving Robustness using Joint Attention Network For Detecting Retinal Degeneration From Optical Coherence Tomography Images

论文

code

8.Matching the Clinical Reality: Accurate OCT-Based Diagnosis From Few Labels

论文

code

5-3.阿尔兹海默症检测

1.The Alzheimer's Disease Prediction Of Longitudinal Evolution (TADPOLE) Challenge: Results after 1 Year Follow-up

论文

code

2.The Effect of Heterogeneous Data for Alzheimer's Disease Detection from Speech

论文

code

3.Preclinical Stage Alzheimer's Disease Detection Using Magnetic Resonance Image Scans

论文

code

4.Convolutional neural networks for Alzheimer’s disease detection on MRI images

论文

code

5. MRI-based Multi-task Decoupling Learning for Alzheimer's Disease Detection and MMSE Score Prediction: A Multi-site Validation

论文

code

6.Feature robustness and sex differences in medical imaging: a case study in MRI-based Alzheimer's disease detection

论文

code

5-4.血细胞计数

1.Machine learning approach of automatic identification and counting of blood cells

论文

code

2.AIDeveloper: deep learning image classification in life science and beyond

论文

code

5-5.胸部疾病分类

1.CheXNet: Radiologist-Level Pneumonia Detection on Chest X-Rays with Deep Learning

论文

code

2.Jointly Learning Convolutional Representations to Compress Radiological Images and Classify Thoracic Diseases in the Compressed Domain

论文

code

6.医学图像分类

6-1.医学图像分类

1.Deep Residual Learning for Image Recognition

论文

code

2.Densely Connected Convolutional Networks

论文

code

3.EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks

论文

code

4.Res2Net: A New Multi-scale Backbone Architecture

论文

code

5.Recurrent Residual Convolutional Neural Network based on U-Net (R2U-Net) for Medical Image Segmentation

论文

code

6.ResNet strikes back: An improved training procedure in timm

论文

code

7.Contrastive Learning of Medical Visual Representations from Paired Images and Text

论文

code

8.Large-scale Robust Deep AUC Maximization: A New Surrogate Loss and Empirical Studies on Medical Image Classification

论文

code

9.RegNet: Self-Regulated Network for Image Classification

论文

code

10.Attention Gated Networks: Learning to Leverage Salient Regions in Medical Images

论文

code

11.Tensor Networks for Medical Image Classification

论文

code

12.Co-Correcting: Noise-tolerant Medical Image Classification via mutual Label Correction

论文

code

13.Synthetic Medical Images from Dual Generative Adversarial Networks

论文

code

14.Capsule Networks against Medical Imaging Data Challenges

论文

code

15.Evolutionary Neural AutoML for Deep Learning

论文

code

6-2.半监督医学图像分类

1.Semi-Supervised Deep Learning for Abnormality Classification in Retinal Images

论文

code

2.In Defense of Pseudo-Labeling: An Uncertainty-Aware Pseudo-label Selection Framework for Semi-Supervised Learning

论文

code

3.Self-supervised Mean Teacher for Semi-supervised Chest X-ray Classification

论文

code

4.Federated Semi-supervised Medical Image Classification via Inter-client Relation Matching

论文

code

5.ACPL: Anti-curriculum Pseudo-labelling for Semi-supervised Medical Image Classification

论文

code

7.COVID-19（新冠肺炎）诊断

1.COVID-CT-Dataset: A CT Scan Dataset about COVID-19

论文

code

2.COVID-Net: A Tailored Deep Convolutional Neural Network Design for Detection of COVID-19 Cases from Chest X-Ray Images

论文

code

3.COVID-19 Image Data Collection

论文

code

4.A Critic Evaluation of Methods for COVID-19 Automatic Detection from X-Ray Images

论文

code

5.Exploring Automatic Diagnosis of COVID-19 from Crowdsourced Respiratory Sound Data

论文

code

6.COVID-CAPS: A Capsule Network-based Framework for Identification of COVID-19 cases from X-ray Images

论文

code

7.Deep Learning COVID-19 Features on CXR using Limited Training Data Sets

论文

code

8.A Deep Convolutional Neural Network for COVID-19 Detection Using Chest X-Rays

论文

code

9.Exploration of Interpretability Techniques for Deep COVID-19 Classification using Chest X-ray Images

论文

code

10.A Fully Automated Deep Learning-based Network For Detecting COVID-19 from a New And Large Lung CT Scan Dataset

论文

code

11.Deep Learning Based Automated COVID-19 Classification from Computed Tomography Images

论文

code

12.Deep Learning Based Automated COVID-19 Classification from Computed Tomography Images

论文

code

13.Can AI help in screening Viral and COVID-19 pneumonia?

论文

code

14.AI4COVID-19: AI Enabled Preliminary Diagnosis for COVID-19 from Cough Samples via an App

论文

code

15.Harmony-Search and Otsu based System for Coronavirus Disease (COVID-19) Detection using Lung CT Scan Images

论文

code

8.医学影像配准

8-1.医学影像配准

1.VoxelMorph: A Learning Framework for Deformable Medical Image Registration

论文

code

2.Unsupervised 3D End-to-End Medical Image Registration with Volume Tweening Network

论文

code

3.Recursive Cascaded Networks for Unsupervised Medical Image Registration

论文

code

4.An Unsupervised Learning Model for Deformable Medical Image Registration

论文

code

5.AirLab: Autograd Image Registration Laboratory

论文

code

6.Networks for Joint Affine and Non-parametric Image Registration

论文

code

7.Enhancing Medical Image Registration via Appearance Adjustment Networks

论文

code

8.GRADICON：: Approximate Diffeomorphisms via Gradient Inverse Consistency

论文

code

9.Deformable medical image registration: setting the state of the art with discrete methods

论文

code

10.An Artificial Agent for Robust Image Registration

论文

code

11.Fast and Robust Symmetric Image Registration Based on Distances Combining Intensity and Spatial Information

论文

code

12.Benchmarking of image registration methods for differently stained histological slides

论文

code

13.FAIM -- A ConvNet Method for Unsupervised 3D Medical Image Registration

论文

code

14.Unsupervised Learning of Probabilistic Diffeomorphic Registration for Images and Surfaces

论文

code

15.Recursive Cascaded Networks for Unsupervised Medical Image Registration

论文

code

8-2.微分胚医学影像配准

1.VoxelMorph: A Learning Framework for Deformable Medical Image Registration

论文

code

2.Symmetric diffeomorphic image registration with cross-correlation: evaluating automated labeling of elderly and neurodegenerative brain

论文

code

3.Unsupervised Learning of Probabilistic Diffeomorphic Registration for Images and Surfaces

论文

code

4.Metric Learning for Image Registration

论文

code

5.Direct cortical thickness estimation using deep learning‐based anatomy segmentation and cortex parcellation

论文

code

6.Reliable brain morphometry from contrast‐enhanced T1w‐MRI in patients with multiple sclerosis

论文

code

8-3.BIRL

1.Consistent and elastic registration of histological sections using vector-spline regularization

论文

code

2.Symmetric diffeomorphic image registration with cross-correlation: evaluating automated labeling of elderly and neurodegenerative brain

论文

code

3.Deformable medical image registration: setting the state of the art with discrete methods

论文

code

4.Benchmarking of image registration methods for differently stained histological slides

论文

code

5.BIRL: Benchmark on Image Registration methods with Landmark validation

论文

code

9.流行病学

1.Did You Really Just Have a Heart Attack? Towards Robust Detection of Personal Health Mentions in Social Media

论文

code

2.Correspondence Analysis Using Neural Networks

论文

code

3.Multi-task Learning for Aggregated Data using Gaussian Processes

论文

code

4.Simulation-Based Inference for Global Health Decisions

论文

code

5.EpidemiOptim: A Toolbox for the Optimization of Control Policies in Epidemiological Models

论文

code

6.Guided Deep List: Automating the Generation of Epidemiological Line Lists from Open Sources

论文

code

7.GeoDict: an integrated gazetteer

论文

code

8.Three faces of node importance in network epidemiology: Exact results for small graphs

论文

code

9.Spatio-Temporal Data Mining: A Survey of Problems and Methods

论文

code

10.Uncertainty-aware generative models for inferring document class prevalence

论文

code

11.Forecasting Treatment Responses Over Time Using Recurrent Marginal Structural Networks

论文

code

12.A Bayesian Monte Carlo approach for predicting the spread of infectious diseases

论文

code

13.Efficient comparison of independence structures of log-linear models

论文

code

14.Distilling Importance Sampling for Likelihood Free Inference

论文

code

15.Parameter elimination in particle Gibbs sampling

论文

code

10.癌症

10-1.乳腺癌检测

1.BreastScreening: On the Use of Multi-Modality in Medical Imaging Diagnosis

论文

code

2.Deep Learning to Improve Breast Cancer Early Detection on Screening Mammography

论文

code

3.Deep Convolutional Neural Networks for Breast Cancer Histology Image Analysis

论文

code

4.High-Resolution Breast Cancer Screening with Multi-View Deep Convolutional Neural Networks

论文

code

5.Deep Neural Networks Improve Radiologists' Performance in Breast Cancer Screening

论文

code

6.Detecting and classifying lesions in mammograms with Deep Learning

论文

code

7.On Breast Cancer Detection: An Application of Machine Learning Algorithms on the Wisconsin Diagnostic Dataset

论文

code

8.Conditional Infilling GANs for Data Augmentation in Mammogram Classification

论文

code

9.Regression Concept Vectors for Bidirectional Explanations in Histopathology

论文

code

10.Utilizing Automated Breast Cancer Detection to Identify Spatial Distributions of Tumor Infiltrating Lymphocytes in Invasive Breast Cancer

论文

code

11.An interpretable classifier for high-resolution breast cancer screening images utilizing weakly supervised localization

论文

code

12.Differences between human and machine perception in medical diagnosis

论文

code

13.Curvature-based Feature Selection with Application in Classifying Electronic Health Records

论文

code

14.O2PF: Oversampling via Optimum-Path Forest for Breast Cancer Detection

论文

code

15.Machine Learning-Based Approaches For Breast Cancer Detection in Microwave Imaging

论文

code

10-2.皮肤癌分类

1.Knowledge Transfer for Melanoma Screening with Deep Learning

论文

code

2.Skin Lesion Synthesis with Generative Adversarial Networks

论文

code

3.Data Augmentation for Skin Lesion Analysis

论文

code

4.Skin Cancer Segmentation and Classification with NABLA-N and Inception Recurrent Residual Convolutional Networks

论文

code

5.Deep neural network or dermatologist?

论文

code

6.Melanoma Detection using Adversarial Training and Deep Transfer Learning

论文

code

7.Convolutional Neural Networks for Classifying Melanoma Images

论文

code

8.Model Patching: Closing the Subgroup Performance Gap with Data Augmentation

论文

code

9.Semi-Supervised Federated Peer Learning for Skin Lesion Classification

论文

code

10.Soft-Attention Improves Skin Cancer Classification Performance

论文

code

11.Skin Deep Unlearning: Artefact and Instrument Debiasing in the Context of Melanoma Classification

论文

code

12.Enabling Data Diversity: Efficient Automatic Augmentation via Regularized Adversarial Training

论文

code

10-3.乳腺癌组织学图像分类

1.Deep Convolutional Neural Networks for Breast Cancer Histology Image Analysis

论文

code

2.Two-Stage Convolutional Neural Network for Breast Cancer Histology Image Classification

论文

code

3.Regression Concept Vectors for Bidirectional Explanations in Histopathology

论文

code

4.Magnification Generalization for Histopathology Image Embedding

论文

code

5.VGGIN-Net: Deep Transfer Network for Imbalanced Breast Cancer Dataset

论文

code

6.BCI: Breast Cancer Immunohistochemical Image Generation through Pyramid Pix2pix

论文

code

10-4.肺癌诊断

1.Encoding Visual Attributes in Capsules for Explainable Medical Diagnoses

论文

code

2.Classification and mutation prediction from non–small cell lung cancer histopathology images using deep learning

论文

code

3.Synthetic Lung Nodule 3D Image Generation Using Autoencoders

论文

code

4.Pathologist-level classification of histologic patterns on resected lung adenocarcinoma slides with deep neural networks

论文

code

5.Knowledge-based Analysis for Mortality Prediction from CT Images

论文

code

6.Time-distance vision transformers in lung cancer diagnosis from longitudinal computed tomography

论文

code

11.死亡率预测

11-1.死亡率预测

1.Multitask learning and benchmarking with clinical time series data

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2.Efficient nonparametric statistical inference on population feature importance using Shapley values

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3.MIMIC-III, a freely accessible critical care database

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4.Interpretable Outcome Prediction with Sparse Bayesian Neural Networks in Intensive Care

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5.Interpretable Outcome Prediction with Sparse Bayesian Neural Networks in Intensive Care

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6.Using Clinical Notes with Time Series Data for ICU Management

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7.Benchmarking machine learning models on multi-centre eICU critical care dataset

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8.Neural Document Embeddings for Intensive Care Patient Mortality Prediction

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9.Benchmark of Deep Learning Models on Large Healthcare MIMIC Datasets

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10.Early hospital mortality prediction using vital signals

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11.Countdown Regression: Sharp and Calibrated Survival Predictions

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12.Interpretable Patient Mortality Prediction with Multi-value Rule Sets

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13.Dynamic Measurement Scheduling for Event Forecasting using Deep RL

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14.Knowledge-based Analysis for Mortality Prediction from CT Images

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15.Analysis | OPEN | Published: 17 June 2019 Multitask learning and benchmarking with clinical time series data

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11-2.ICU死亡率

1.Dynamic Measurement Scheduling for Event Forecasting using Deep RL

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2.ISeeU2: Visually Interpretable ICU mortality prediction using deep learning and free-text medical notes

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3.HiRID-ICU-Benchmark -- A Comprehensive Machine Learning Benchmark on High-resolution ICU Data

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4.FLICU: A Federated Learning Workflow for Intensive Care Unit Mortality Prediction

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5.Early prediction of the risk of ICU mortality with Deep Federated Learning

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12.疾病预测

12-1.疾病预测

1.A Scheme for Continuous Input to the Tsetlin Machine with Applications to Forecasting Disease Outbreaks

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2.The Alzheimer's Disease Prediction Of Longitudinal Evolution (TADPOLE) Challenge: Results after 1 Year Follow-up

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3.Learning Representations of Ultrahigh-dimensional Data for Random Distance-based Outlier Detection

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4.Naive Bayes and Text Classification I - Introduction and Theory

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5.VTGAN: Semi-supervised Retinal Image Synthesis and Disease Prediction using Vision Transformers

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6.Unsupervised Pre-Training on Patient Population Graphs for Patient-Level Predictions

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7.Heart Disease Prediction System using Associative Classification and Genetic Algorithm

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8.Spectral Graph Convolutions for Population-based Disease Prediction

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9.Robust Multiple Kernel k-means Clustering using Min-Max Optimization

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10.Disease Prediction using Graph Convolutional Networks: Application to Autism Spectrum Disorder and Alzheimer's Disease

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11.Deep EHR: Chronic Disease Prediction Using Medical Notes

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12.TADPOLE Challenge: Prediction of Longitudinal Evolution in Alzheimer's Disease

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13.MiME: Multilevel Medical Embedding of Electronic Health Records for Predictive Healthcare

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14.An overview of deep learning in medical imaging focusing on MRI

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15.Chester: A Web Delivered Locally Computed Chest X-Ray Disease Prediction System

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12-2.疾病轨迹预测

1.RETAIN: An Interpretable Predictive Model for Healthcare using Reverse Time Attention Mechanism

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2.CLIMAT: Clinically-Inspired Multi-Agent Transformers for Knee Osteoarthritis Trajectory Forecasting

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3.Learning Dynamic and Personalized Comorbidity Networks from Event Data using Deep Diffusion Processes

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4.Clinically-Inspired Multi-Agent Transformers for Disease Trajectory Forecasting from Multimodal Data

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13.睡眠质量

13-1.睡眠阶段检测

1.DeepSleepNet: a Model for Automatic Sleep Stage Scoring based on Raw Single-Channel EEG

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2.SleepEEGNet: Automated Sleep Stage Scoring with Sequence to Sequence Deep Learning Approach

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3.An Open-source Toolbox for Analysing and Processing PhysioNet Databases in MATLAB and Octave

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4.SeqSleepNet: End-to-End Hierarchical Recurrent Neural Network for Sequence-to-Sequence Automatic Sleep Staging

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5.Real-Time Sleep Staging using Deep Learning on a Smartphone for a Wearable EEG

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6.Intra- and Inter-epoch Temporal Context Network (IITNet) Using Sub-epoch Features for Automatic Sleep Scoring on Raw Single-channel EEG

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7.Dreem Open Datasets: Multi-Scored Sleep Datasets to compare Human and Automated sleep staging

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8.Joint Classification and Prediction CNN Framework for Automatic Sleep Stage Classification

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9.Towards More Accurate Automatic Sleep Staging via Deep Transfer Learning

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10.REST: Robust and Efficient Neural Networks for Sleep Monitoring in the Wild

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11.An Attention-Based Deep Learning Approach for Sleep Stage Classification With Single-Channel EEG

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12.ADAST: Attentive Cross-domain EEG-based Sleep Staging Framework with Iterative Self-Training

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13.A Deep Knowledge Distillation framework for EEG assisted enhancement of single-lead ECG based sleep staging

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14.Do Not Sleep on Traditional Machine Learning: Simple and Interpretable Techniques Are Competitive to Deep Learning for Sleep Scoring

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13-2.睡眠质量

1.DOSED: a deep learning approach to detect multiple sleep micro-events in EEG signal

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2.Deepsleep: Fast and Accurate Delineation of Sleep Arousals at Millisecond Resolution by Deep Learning

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3.An Attention-Based Deep Learning Approach for Sleep Stage Classification With Single-Channel EEG

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4.Quantified Sleep: Machine learning techniques for observational n-of-1 studies

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5.MAUS: A Dataset for Mental Workload Assessmenton N-back Task Using Wearable Sensor

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6.Advanced sleep spindle identification with neural networks

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7.DeepSleep 2.0: Automated Sleep Arousal Segmentation via Deep Learning

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8.A Knowledge Distillation Framework For Enhancing Ear-EEG Based Sleep Staging With Scalp-EEG Data

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13-3.睡眠微事件检测

1.DOSED: a deep learning approach to detect multiple sleep micro-events in EEG signal

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2.Deepsleep: Fast and Accurate Delineation of Sleep Arousals at Millisecond Resolution by Deep Learning

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3.RED: Deep Recurrent Neural Networks for Sleep EEG Event Detection

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4.Advanced sleep spindle identification with neural networks

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5.DeepSleep 2.0: Automated Sleep Arousal Segmentation via Deep Learning

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13-4.睡眠呼吸暂停检测

1.DOSED: a deep learning approach to detect multiple sleep micro-events in EEG signal

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2.Non-contact Infant Sleep Apnea Detection

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3.Learning Realistic Patterns from Unrealistic Stimuli: Generalization and Data Anonymization

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4.A 1D-CNN Based Deep Learning Technique for Sleep Apnea Detection in IoT Sensors

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5.Sleep Apnea Detection From Single-Lead ECG: A Comprehensive Analysis of Machine Learning and Deep Learning Algorithms

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14.蛋白质结构检测

14-1.蛋白质结构预测

1.Highly accurate protein structure prediction with AlphaFold

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2.MUST-CNN: A Multilayer Shift-and-Stitch Deep Convolutional Architecture for Sequence-based Protein Structure Prediction

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3.Accurate Protein Structure Prediction by Embeddings and Deep Learning Representations

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4.SidechainNet: An All-Atom Protein Structure Dataset for Machine Learning

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5.ProteinNet: a standardized data set for machine learning of protein structure

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6.Distribution-Free, Risk-Controlling Prediction Sets

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7.Iterative SE(3)-Transformers

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8.HelixFold: An Efficient Implementation of AlphaFold2 using PaddlePaddle

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9.Deep Supervised and Convolutional Generative Stochastic Network for Protein Secondary Structure Prediction

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10.How pairwise coevolutionary models capture the collective residue variability in proteins

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11.Universal Transforming Geometric Network

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12.PolyFold: an interactive visual simulator for distance-based protein folding

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13.Generating Tertiary Protein Structures via an Interpretative Variational Autoencoder

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14.Energy-based models for atomic-resolution protein conformations

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15.FastFold: Reducing AlphaFold Training Time from 11 Days to 67 Hours

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14-2.蛋白质界面预测

1.Protein Interface Prediction using Graph Convolutional Networks

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2.End-to-End Learning on 3D Protein Structure for Interface Prediction

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3.DIPS-Plus: The Enhanced Database of Interacting Protein Structures for Interface Prediction

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4.When Geometric Deep Learning Meets Pretrained Protein Language Models

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15.肌电图（EMG）

15-1.肌电图（EMG）

1.Parkinson’s Disease EMG Data Augmentation and Simulation with DCGANs and Style Transfer

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2.sEMG Gesture Recognition with a Simple Model of Attention

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3.Boosting Factor-Specific Functional Historical Models for the Detection of Synchronisation in Bioelectrical Signals

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4.EV-Action: Electromyography-Vision Multi-Modal Action Dataset

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5.Parkinson’s Disease EMG Signal Prediction Using Neural Networks

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6.Hardware Implementation of Deep Network Accelerators Towards Healthcare and Biomedical Applications

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7.Digital Voicing of Silent Speech

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8.End-to-end grasping policies for human-in-the-loop robots via deep reinforcement learning

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9.An Improved Model for Voicing Silent Speech

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10.Efficient TMS-Based Motor Cortex Mapping Using Gaussian Process Active Learning

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11.Towards Predicting Fine Finger Motions from Ultrasound Images via Kinematic Representation

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12.neuro2vec: Masked Fourier Spectrum Prediction for Neurophysiological Representation Learning

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13.Dreamento: an open-source dream engineering toolbox for sleep EEG wearables

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15-2.肌电手势识别

1.Deep Learning for Electromyographic Hand Gesture Signal Classification Using Transfer Learning

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2.sEMG Gesture Recognition with a Simple Model of Attention

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3.An EMG Gesture Recognition System with Flexible High-Density Sensors and Brain-Inspired High-Dimensional Classifier

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4.Domain Adaptation for sEMG-based Gesture Recognition with Recurrent Neural Networks

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5.A Transferable Adaptive Domain Adversarial Neural Network for Virtual Reality Augmented EMG-Based Gesture Recognition

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6.Signals to Spikes for Neuromorphic Regulated Reservoir Computing and EMG Hand Gesture Recognition

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16.医学图像生成

1.NiftyNet: a deep-learning platform for medical imaging

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2.Generative Adversarial Networks for Image-to-Image Translation on Multi-Contrast MR Images - A Comparison of CycleGAN and UNIT

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3.PnP-AdaNet: Plug-and-Play Adversarial Domain Adaptation Network with a Benchmark at Cross-modality Cardiac Segmentation

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4.Skin Lesion Synthesis with Generative Adversarial Networks

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5.Towards Adversarial Retinal Image Synthesis

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6.Synthetic Medical Images from Dual Generative Adversarial Networks

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7.Generative Adversarial Network in Medical Imaging: A Review

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8.ADN: Artifact Disentanglement Network for Unsupervised Metal Artifact Reduction

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9.Melanoma Detection using Adversarial Training and Deep Transfer Learning

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10.Image Translation for Medical Image Generation -- Ischemic Stroke Lesions

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11.Evaluating the Clinical Realism of Synthetic Chest X-Rays Generated Using Progressively Growing GANs

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12.MammoGANesis: Controlled Generation of High-Resolution Mammograms for Radiology Education

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13.Overcoming Barriers to Data Sharing with Medical Image Generation: A Comprehensive Evaluation

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14.Explainable Diabetic Retinopathy Detection and Retinal Image Generation

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15.BCI: Breast Cancer Immunohistochemical Image Generation through Pyramid Pix2pix

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17.癫痫发作检测

1.An IoT Endpoint System-on-Chip for Secure and Energy-Efficient Near-Sensor Analytics

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2.SeizureNet: Multi-Spectral Deep Feature Learning for Seizure Type Classification

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3.An Open-source Toolbox for Analysing and Processing PhysioNet Databases in MATLAB and Octave

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4.Learning Robust Features using Deep Learning for Automatic Seizure Detection

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5.Change Detection in Graph Streams by Learning Graph Embeddings on Constant-Curvature Manifolds

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6.Seizure Type Classification using EEG signals and Machine Learning: Setting a benchmark

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7.Synthetic Epileptic Brain Activities Using Generative Adversarial Networks

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8.Adversarial Representation Learning for Robust Patient-Independent Epileptic Seizure Detection

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9.Semi-Supervised Learning for Sparsely-Labeled Sequential Data: Application to Healthcare Video Processing

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10.Self-Supervised Graph Neural Networks for Improved Electroencephalographic Seizure Analysis

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11.Systematic Assessment of Hyperdimensional Computing for Epileptic Seizure Detection

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12.Efficient Epileptic Seizure Detection Using CNN-Aided Factor Graphs

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13.Multi-Centroid Hyperdimensional Computing Approach for Epileptic Seizure Detection

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14.Scalable Machine Learning Architecture for Neonatal Seizure Detection on Ultra-Edge Devices

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15.Real-Time Seizure Detection using EEG: A Comprehensive Comparison of Recent Approaches under a Realistic Setting

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18.肺炎检测

1.CheXNet: Radiologist-Level Pneumonia Detection on Chest X-Rays with Deep Learning

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2.Exploration of Interpretability Techniques for Deep COVID-19 Classification using Chest X-ray Images

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3.Jointly Learning Convolutional Representations to Compress Radiological Images and Classify Thoracic Diseases in the Compressed Domain

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4.Multi-Objective Evolutionary Design of Deep Convolutional Neural Networks for Image Classification

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5.MUXConv: Information Multiplexing in Convolutional Neural Networks

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6.Deep Learning for Automatic Pneumonia Detection

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7.COVID-CXNet: Detecting COVID-19 in Frontal Chest X-ray Images using Deep Learning

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8.CovXNet: A multi-dilation convolutional neural network for automatic COVID-19 and other pneumonia detection from chest X-ray images with transferable multi-receptive feature optimization

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9.MetaCOVID: A Siamese neural network framework with contrastive loss for n-shot diagnosis of COVID-19 patients

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10.The pitfalls of using open data to develop deep learning solutions for COVID-19 detection in chest X-rays

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11.COVID-19 Pneumonia and Influenza Pneumonia Detection Using Convolutional Neural Networks

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12.Image quality assessment for machine learning tasks using meta-reinforcement learning