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 271–280 of 424 papers

Title	Date	Tasks	Status
OpenMedIA: Open-Source Medical Image Analysis Toolbox and Benchmark under Heterogeneous AI Computing Platforms	Aug 11, 2022	image-classificationImage Classification	—Unverified
Optimizing Federated Learning for Medical Image Classification on Distributed Non-iid Datasets with Partial Labels	Mar 10, 2023	Federated Learningimage-classification	—Unverified
ParseCaps: An Interpretable Parsing Capsule Network for Medical Image Diagnosis	Nov 3, 2024	image-classificationImage Classification	—Unverified
PCCT: Progressive Class-Center Triplet Loss for Imbalanced Medical Image Classification	Jul 11, 2022	image-classificationImage Classification	—Unverified
Plug-and-Play Feature Generation for Few-Shot Medical Image Classification	Oct 14, 2023	Few-Shot Learningimage-classification	—Unverified
PM2: A New Prompting Multi-modal Model Paradigm for Few-shot Medical Image Classification	Apr 13, 2024	ClassificationFew-Shot Learning	—Unverified
Point-of-Care Diabetic Retinopathy Diagnosis: A Standalone Mobile Application Approach	Jan 26, 2020	Deep LearningDiagnostic	—Unverified
Pyramid Pixel Context Adaption Network for Medical Image Classification with Supervised Contrastive Learning	Mar 3, 2023	Contrastive LearningDecision Making	—Unverified
Predictive uncertainty estimation in deep learning for lung carcinoma classification in digital pathology under real dataset shifts	Aug 15, 2024	Decision MakingDiagnostic	—Unverified
Privacy-Preserving Constrained Domain Generalization via Gradient Alignment	May 14, 2021	ClassificationDomain Generalization	—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