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 191–200 of 424 papers

Title	Date	Tasks	Status
Aligning Human Knowledge with Visual Concepts Towards Explainable Medical Image Classification	Jun 8, 2024	Decision MakingDiagnostic	—Unverified
Compute-Efficient Medical Image Classification with Softmax-Free Transformers and Sequence Normalization	Jun 3, 2024	image-classificationImage Classification	—Unverified
CONFINE: Conformal Prediction for Interpretable Neural Networks	Jun 1, 2024	Conformal Predictionimage-classification	—Unverified
GenMix: Combining Generative and Mixture Data Augmentation for Medical Image Classification	May 31, 2024	Data AugmentationDiversity	—Unverified
MoVL:Exploring Fusion Strategies for the Domain-Adaptive Application of Pretrained Models in Medical Imaging Tasks	May 13, 2024	image-classificationImage Classification	—Unverified
A Lightweight Neural Architecture Search Model for Medical Image Classification	May 6, 2024	Deep Learningimage-classification	—Unverified
Meta-Transfer Derm-Diagnosis: Exploring Few-Shot Learning and Transfer Learning for Skin Disease Classification in Long-Tail Distribution	Apr 25, 2024	Data AugmentationFew-Shot Learning	—Unverified
Brain Storm Optimization Based Swarm Learning for Diabetic Retinopathy Image Classification	Apr 24, 2024	Federated Learningimage-classification	—Unverified
A review of deep learning-based information fusion techniques for multimodal medical image classification	Apr 23, 2024	image-classificationImage Classification	—Unverified
Distributed Federated Learning-Based Deep Learning Model for Privacy MRI Brain Tumor Detection	Apr 15, 2024	DiagnosticFederated Learning	—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