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

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Showing 161–170 of 424 papers

Title	Date	Tasks	Status
Expert-Like Reparameterization of Heterogeneous Pyramid Receptive Fields in Efficient CNNs for Fair Medical Image Classification	May 19, 2025	Fairnessimage-classification	—Unverified
Evolution-aware VAriance (EVA) Coreset Selection for Medical Image Classification	Jun 9, 2024	image-classificationImage Classification	—Unverified
Applications of Sequential Learning for Medical Image Classification	Sep 26, 2023	Classificationimage-classification	—Unverified
EVM-Fusion: An Explainable Vision Mamba Architecture with Neural Algorithmic Fusion	May 23, 2025	Decision Makingimage-classification	—Unverified
Evaluating the Fairness of Neural Collapse in Medical Image Classification	Jul 8, 2024	Deep LearningFairness	—Unverified
Chest X-rays Classification: A Multi-Label and Fine-Grained Problem	Jul 19, 2018	General Classificationimage-classification	—Unverified
Explaining Clinical Decision Support Systems in Medical Imaging using Cycle-Consistent Activation Maximization	Oct 9, 2020	Breast Cancer DetectionDecision Making	—Unverified
Explanations of Classifiers Enhance Medical Image Segmentation via End-to-end Pre-training	Jan 16, 2024	image-classificationImage Classification	—Unverified
Exploring Low-Resource Medical Image Classification with Weakly Supervised Prompt Learning	Feb 6, 2024	Few-Shot Learningimage-classification	—Unverified
A ChatGPT Aided Explainable Framework for Zero-Shot Medical Image Diagnosis	Jul 5, 2023	Diagnosticimage-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