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 361–370 of 424 papers

Title	Date	Tasks	Status
Unleashing the Potential of Open-set Noisy Samples Against Label Noise for Medical Image Classification	Jun 18, 2024	Classificationimage-classification	—Unverified
Deeply Supervised Layer Selective Attention Network: Towards Label-Efficient Learning for Medical Image Classification	Sep 28, 2022	feature selectionimage-classification	—Unverified
Secure Diagnostics: Adversarial Robustness Meets Clinical Interpretability	Apr 7, 2025	Adversarial AttackAdversarial Robustness	—Unverified
Detecção da Psoríase Utilizando Visão Computacional: Uma Abordagem Comparativa Entre CNNs e Vision Transformers	Jun 11, 2025	image-classificationImage Classification	—Unverified
Aggregative Self-Supervised Feature Learning from a Limited Sample	Dec 14, 2020	image-classificationImage Classification	—Unverified
A Fully Convolutional Normalization Approach of Head and Neck Cancer Outcome Prediction	Jan 25, 2020	image-classificationImage Classification	—Unverified
Development of CNN Architectures using Transfer Learning Methods for Medical Image Classification	Oct 22, 2024	ClassificationDeep Learning	—Unverified
Diagnosis and Analysis of Celiac Disease and Environmental Enteropathy on Biopsy Images using Deep Learning Approaches	Jun 11, 2020	image-classificationImage Classification	—Unverified
Diff3Dformer: Leveraging Slice Sequence Diffusion for Enhanced 3D CT Classification with Transformer Networks	Jun 24, 2024	3D ClassificationClassification	—Unverified
Unsupervised Deep Transfer Feature Learning for Medical Image Classification	Mar 15, 2019	ClassificationGeneral Classification	—Unverified

Show:10 25 50

← PrevPage 37 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