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

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 71–80 of 424 papers

Title	Date	Tasks	Status	Hype
Systematic comparison of semi-supervised and self-supervised learning for medical image classification	Jul 18, 2023	GPUimage-classification	CodeCode Available	1
Explainable Deep Learning Methods in Medical Image Classification: A Survey	May 10, 2022	Deep LearningExplainable artificial intelligence	CodeCode Available	1
Failure Detection in Medical Image Classification: A Reality Check and Benchmarking Testbed	May 27, 2022	BenchmarkingBinary Classification	CodeCode Available	1
Fair Federated Medical Image Classification Against Quality Shift via Inter-Client Progressive State Matching	Mar 12, 2025	FairnessFederated Learning	CodeCode Available	1
Federated Semi-supervised Medical Image Classification via Inter-client Relation Matching	Jun 16, 2021	Federated Learningimage-classification	CodeCode Available	1
FedMLP: Federated Multi-Label Medical Image Classification under Task Heterogeneity	Jun 27, 2024	Federated Learningimage-classification	CodeCode Available	1
Mixture Outlier Exposure: Towards Out-of-Distribution Detection in Fine-grained Environments	Jun 7, 2021	image-classificationImage Classification	CodeCode Available	1
Fine-Grained Self-Supervised Learning with Jigsaw Puzzles for Medical Image Classification	Aug 10, 2023	image-classificationImage Classification	CodeCode Available	1
Malaria Parasite Detection using Efficient Neural Ensembles	Oct 15, 2021	DiagnosticMedical Image Classification	CodeCode Available	1
Rethinking Transfer Learning for Medical Image Classification	Jun 9, 2021	Classificationimage-classification	CodeCode Available	1

Show:10 25 50

← PrevPage 8 of 43Next →

All datasets NCT-CRC-HE-100K IDRiD ImageNet PCOS Classification CheXphoto Galaxy10 DECals ISIC 2017 ISIC 2020 Challenge Dataset Malaria Dataset OASIS 3

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	Efficientnet-b0	Accuracy (%)	95.59	—	Unverified
2	ResNeXt-50-32x4d	Accuracy (%)	95.46	—	Unverified
3	RegNetY-3.2GF	Accuracy (%)	95.42	—	Unverified
4	ResNet-50	Accuracy (%)	94.72	—	Unverified
5	DenseNet-169	Accuracy (%)	94.41	—	Unverified
6	Res2Net-50	Accuracy (%)	93.37	—	Unverified
7	ResNet-18	Accuracy (%)	92.66	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	ResNet-152	Accuracy (% )	86.56	—	Unverified
2	Beta-Rank	Accuracy	81.88	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	DaViT-S	GFLOPs	8.8	—	Unverified
2	DaViT-T	GFLOPs	4.5	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	InceptionV3	1:1 Accuracy	90.2	—	Unverified
2	EfficientNet B7	1:1 Accuracy	88.9	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	PTRN	Mean AUC	0.85	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Astroformer	Top-1 Accuracy (%)	94.87	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Beta-Rank	Accuracy	72.44	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	EfficientNet Ensemble	AUC	0.95	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	SNAPSHOT ENSEMBLE	F1 score	99.37	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	3D CNN	AUC	87	—	Unverified