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 151–160 of 424 papers

Title	Date	Tasks	Status	Score
Improving the repeatability of deep learning models with Monte Carlo dropout	Feb 15, 2022	AttributeBinary Classification	CodeCode Available	5
Improving Generalizability of Kolmogorov-Arnold Networks via Error-Correcting Output Codes	May 9, 2025	Classificationimage-classification	CodeCode Available	5
Integrating kNN with Foundation Models for Adaptable and Privacy-Aware Image Classification	Feb 19, 2024	ClassificationContinual Learning	CodeCode Available	5
A Parameterized Generative Adversarial Network Using Cyclic Projection for Explainable Medical Image Classification	Nov 24, 2023	Data AugmentationGenerative Adversarial Network	CodeCode Available	5
Enhancing Multimodal Medical Image Classification using Cross-Graph Modal Contrastive Learning	Oct 23, 2024	ClassificationContrastive Learning	CodeCode Available	5
Homogeneous Learning: Self-Attention Decentralized Deep Learning	Oct 11, 2021	Deep LearningFederated Learning	CodeCode Available	5
Chest X-Ray Images Classification with CNN	Dec 31, 2022	ClassificationDiagnostic	CodeCode Available	5
Estimating the Conformal Prediction Threshold from Noisy Labels	Jan 22, 2025	Conformal Predictionimage-classification	CodeCode Available	5
ISLE: An Intelligent Streaming Framework for High-Throughput AI Inference in Medical Imaging	May 24, 2023	Decision MakingImage Classification	CodeCode Available	5
HDKD: Hybrid Data-Efficient Knowledge Distillation Network for Medical Image Classification	Jul 10, 2024	Computational Efficiencyimage-classification	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