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 111–120 of 424 papers

Title	Date	Tasks	Status	Score
Automatic Acne Object Detection and Acne Severity Grading Using Smartphone Images and Artificial Intelligence	Aug 3, 2022	Acne Severity GradingMedical Image Classification	CodeCode Available	5
Integrating kNN with Foundation Models for Adaptable and Privacy-Aware Image Classification	Feb 19, 2024	ClassificationContinual Learning	CodeCode Available	5
Automated Web-Based Malaria Detection System with Machine Learning and Deep Learning Techniques: A Comparative Analysis	Jun 27, 2024	Medical Image ClassificationTransfer Learning	CodeCode Available	5
KPL: Training-Free Medical Knowledge Mining of Vision-Language Models	Jan 20, 2025	Classificationimage-classification	CodeCode Available	5
Beta-Rank: A Robust Convolutional Filter Pruning Method For Imbalanced Medical Image Analysis	Apr 15, 2023	Image ClassificationMedical Image Analysis	CodeCode Available	5
Contrastive-Based Deep Embeddings for Label Noise-Resilient Histopathology Image Classification	Apr 11, 2024	Contrastive LearningDeep Learning	CodeCode Available	5
Attention Gated Networks: Learning to Leverage Salient Regions in Medical Images	Aug 22, 2018	Computational EfficiencyGeneral Classification	CodeCode Available	5
Connecting the Dots: Graph Neural Network Powered Ensemble and Classification of Medical Images	Nov 13, 2023	BenchmarkingClassification	CodeCode Available	5
Improving Generalizability of Kolmogorov-Arnold Networks via Error-Correcting Output Codes	May 9, 2025	Classificationimage-classification	CodeCode Available	5
ConDiSR: Contrastive Disentanglement and Style Regularization for Single Domain Generalization	Mar 14, 2024	ClassificationDisentanglement	CodeCode Available	5

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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