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 161–170 of 424 papers

Title	Date	Tasks	Status
Visual Prompt Engineering for Medical Vision Language Models in Radiology	Aug 28, 2024	Classificationimage-classification	—Unverified
Text-guided Foundation Model Adaptation for Long-Tailed Medical Image Classification	Aug 27, 2024	DiagnosticGPU	—Unverified
Uncertainties of Latent Representations in Computer Vision	Aug 26, 2024	image-classificationImage Classification	—Unverified
Cervical Cancer Detection Using Multi-Branch Deep Learning Model	Aug 20, 2024	ClassificationDeep Learning	—Unverified
Predictive uncertainty estimation in deep learning for lung carcinoma classification in digital pathology under real dataset shifts	Aug 15, 2024	Decision MakingDiagnostic	—Unverified
PRECISe : Prototype-Reservation for Explainable Classification under Imbalanced and Scarce-Data Settings	Aug 11, 2024	image-classificationImage Classification	CodeCode Available
A Novel Momentum-Based Deep Learning Techniques for Medical Image Classification and Segmentation	Aug 11, 2024	Benchmarkingimage-classification	—Unverified
Dual-View Pyramid Pooling in Deep Neural Networks for Improved Medical Image Classification and Confidence Calibration	Aug 6, 2024	Classificationimage-classification	—Unverified
Deep Learning in Medical Image Classification from MRI-based Brain Tumor Images	Aug 1, 2024	Brain Tumor ClassificationDecision Making	—Unverified
UniFed: A Universal Federation of a Mixture of Highly Heterogeneous Medical Image Classification Tasks	Jul 29, 2024	Federated Learningimage-classification	CodeCode Available

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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