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 211–220 of 424 papers

Title	Date	Tasks	Status	Hype
Vision Through the Veil: Differential Privacy in Federated Learning for Medical Image Classification	Jun 30, 2023	Federated Learningimage-classification	—Unverified	0
PCDAL: A Perturbation Consistency-Driven Active Learning Approach for Medical Image Segmentation and Classification	Jun 29, 2023	Active LearningClassification	CodeCode Available	0
MedFMC: A Real-world Dataset and Benchmark For Foundation Model Adaptation in Medical Image Classification	Jun 16, 2023	Diabetic Retinopathy Gradingimage-classification	CodeCode Available	2
Label-noise-tolerant medical image classification via self-attention and self-supervised learning	Jun 16, 2023	Contrastive Learningimage-classification	—Unverified	0
Active Globally Explainable Learning for Medical Images via Class Association Embedding and Cyclic Adversarial Generation	Jun 12, 2023	counterfactualExplainable Artificial Intelligence (XAI)	—Unverified	0
Preserving privacy in domain transfer of medical AI models comes at no performance costs: The integral role of differential privacy	Jun 10, 2023	DiagnosticDomain Generalization	CodeCode Available	0
Exploring the Versatility of Zero-Shot CLIP for Interstitial Lung Disease Classification	Jun 1, 2023	ClassificationDiagnostic	—Unverified	0
FoPro-KD: Fourier Prompted Effective Knowledge Distillation for Long-Tailed Medical Image Recognition	May 27, 2023	image-classificationImage Classification	CodeCode Available	1
ISLE: An Intelligent Streaming Framework for High-Throughput AI Inference in Medical Imaging	May 24, 2023	Decision MakingImage Classification	CodeCode Available	0
Medical supervised masked autoencoders: Crafting a better masking strategy and efficient fine-tuning schedule for medical image classification	May 10, 2023	Computational Efficiencyimage-classification	CodeCode Available	0

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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