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 131–140 of 424 papers

Title	Date	Tasks	Status
EVM-Fusion: An Explainable Vision Mamba Architecture with Neural Algorithmic Fusion	May 23, 2025	Decision Makingimage-classification	—Unverified
CONFINE: Conformal Prediction for Interpretable Neural Networks	Jun 1, 2024	Conformal Predictionimage-classification	—Unverified
Dual-View Pyramid Pooling in Deep Neural Networks for Improved Medical Image Classification and Confidence Calibration	Aug 6, 2024	Classificationimage-classification	—Unverified
Concept Bottleneck with Visual Concept Filtering for Explainable Medical Image Classification	Aug 23, 2023	image-classificationImage Classification	—Unverified
A Hybrid Fully Convolutional CNN-Transformer Model for Inherently Interpretable Medical Image Classification	Apr 11, 2025	image-classificationImage Classification	—Unverified
Computer vision and machine learning for medical image analysis: recent advances, challenges, and way forward	Mar 21, 2022	image-classificationImage Classification	—Unverified
Compute-Efficient Medical Image Classification with Softmax-Free Transformers and Sequence Normalization	Jun 3, 2024	image-classificationImage Classification	—Unverified
Evaluating the Fairness of Neural Collapse in Medical Image Classification	Jul 8, 2024	Deep LearningFairness	—Unverified
Evolution-aware VAriance (EVA) Coreset Selection for Medical Image Classification	Jun 9, 2024	image-classificationImage Classification	—Unverified
Exploring Low-Resource Medical Image Classification with Weakly Supervised Prompt Learning	Feb 6, 2024	Few-Shot Learningimage-classification	—Unverified

Show:10 25 50

← PrevPage 14 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