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 341–350 of 424 papers

Title	Date	Tasks	Status
A New Perspective to Boost Vision Transformer for Medical Image Classification	Jan 3, 2023	Diabetic Retinopathy Gradingimage-classification	—Unverified
An ensemble framework approach of hybrid Quantum convolutional neural networks for classification of breast cancer images	Sep 24, 2024	image-classificationImage Classification	—Unverified
Rethinking Foundation Models for Medical Image Classification through a Benchmark Study on MedMNIST	Jan 24, 2025	Classificationimage-classification	—Unverified
Analysis of Explainable Artificial Intelligence Methods on Medical Image Classification	Dec 10, 2022	Decision MakingExplainable artificial intelligence	—Unverified
Aligning Human Knowledge with Visual Concepts Towards Explainable Medical Image Classification	Jun 8, 2024	Decision MakingDiagnostic	—Unverified
Review of AlexNet for Medical Image Classification	Nov 15, 2023	Classificationimage-classification	—Unverified
A Test Statistic Estimation-based Approach for Establishing Self-interpretable CNN-based Binary Classifiers	Mar 13, 2023	Binary ClassificationDecoder	—Unverified
Robust and Interpretable Medical Image Classifiers via Concept Bottleneck Models	Oct 4, 2023	Diagnosticimage-classification	—Unverified
A Lightweight Neural Architecture Search Model for Medical Image Classification	May 6, 2024	Deep Learningimage-classification	—Unverified
A Hybrid Fully Convolutional CNN-Transformer Model for Inherently Interpretable Medical Image Classification	Apr 11, 2025	image-classificationImage Classification	—Unverified

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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