SOTAVerified

Medical Image Classification

Medical Image Classification is a task in medical image analysis that involves classifying medical images, such as X-rays, MRI scans, and CT scans, into different categories based on the type of image or the presence of specific structures or diseases. The goal is to use computer algorithms to automatically identify and classify medical images based on their content, which can help in diagnosis, treatment planning, and disease monitoring.

Papers

Showing 401424 of 424 papers

TitleStatusHype
Detection of Dementia Through 3D Convolutional Neural Networks Based on Amyloid PETCode0
Beta-Rank: A Robust Convolutional Filter Pruning Method For Imbalanced Medical Image AnalysisCode0
Detecting Shortcuts in Medical Images -- A Case Study in Chest X-raysCode0
Bayesian Statistics Guided Label Refurbishment Mechanism: Mitigating Label Noise in Medical Image ClassificationCode0
PCDAL: A Perturbation Consistency-Driven Active Learning Approach for Medical Image Segmentation and ClassificationCode0
PEFAT: Boosting Semi-Supervised Medical Image Classification via Pseudo-Loss Estimation and Feature Adversarial TrainingCode0
DenseNet for Breast Tumor Classification in Mammographic ImagesCode0
BayTTA: Uncertainty-aware medical image classification with optimized test-time augmentation using Bayesian model averagingCode0
BSDA: Bayesian Random Semantic Data Augmentation for Medical Image ClassificationCode0
A Parameterized Generative Adversarial Network Using Cyclic Projection for Explainable Medical Image ClassificationCode0
Automatic Acne Object Detection and Acne Severity Grading Using Smartphone Images and Artificial IntelligenceCode0
PRECISe : Prototype-Reservation for Explainable Classification under Imbalanced and Scarce-Data SettingsCode0
Video Capsule Endoscopy Classification using Focal Modulation Guided Convolutional Neural NetworkCode0
Preservation of High Frequency Content for Deep Learning-Based Medical Image ClassificationCode0
Preserving privacy in domain transfer of medical AI models comes at no performance costs: The integral role of differential privacyCode0
Deep Residual Network based Automatic Image Grading for Diabetic Macular EdemaCode0
Deep Modeling and Optimization of Medical Image ClassificationCode0
PRICURE: Privacy-Preserving Collaborative Inference in a Multi-Party SettingCode0
Universal Semi-Supervised Learning for Medical Image ClassificationCode0
Advancements in Medical Image Classification through Fine-Tuning Natural Domain Foundation ModelsCode0
SKID: Self-Supervised Learning for Knee Injury Diagnosis from MRI DataCode0
Private, fair and accurate: Training large-scale, privacy-preserving AI models in medical imagingCode0
Automated Web-Based Malaria Detection System with Machine Learning and Deep Learning Techniques: A Comparative AnalysisCode0
ProCo: Prototype-aware Contrastive Learning for Long-tailed Medical Image ClassificationCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Efficientnet-b0Accuracy (%)95.59Unverified
2ResNeXt-50-32x4dAccuracy (%)95.46Unverified
3RegNetY-3.2GFAccuracy (%)95.42Unverified
4ResNet-50Accuracy (%)94.72Unverified
5DenseNet-169Accuracy (%)94.41Unverified
6Res2Net-50Accuracy (%)93.37Unverified
7ResNet-18Accuracy (%)92.66Unverified
#ModelMetricClaimedVerifiedStatus
1ResNet-152Accuracy (% )86.56Unverified
2Beta-RankAccuracy81.88Unverified
#ModelMetricClaimedVerifiedStatus
1DaViT-SGFLOPs8.8Unverified
2DaViT-TGFLOPs4.5Unverified
#ModelMetricClaimedVerifiedStatus
1InceptionV31:1 Accuracy90.2Unverified
2EfficientNet B71:1 Accuracy88.9Unverified
#ModelMetricClaimedVerifiedStatus
1PTRNMean AUC0.85Unverified
#ModelMetricClaimedVerifiedStatus
1AstroformerTop-1 Accuracy (%)94.87Unverified
#ModelMetricClaimedVerifiedStatus
1Beta-RankAccuracy72.44Unverified
#ModelMetricClaimedVerifiedStatus
1EfficientNet EnsembleAUC0.95Unverified
#ModelMetricClaimedVerifiedStatus
1SNAPSHOT ENSEMBLEF1 score99.37Unverified
#ModelMetricClaimedVerifiedStatus
13D CNNAUC87Unverified