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

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Showing 201–210 of 424 papers

Title	Date	Tasks	Status
GenMix: Combining Generative and Mixture Data Augmentation for Medical Image Classification	May 31, 2024	Data AugmentationDiversity	—Unverified
GPT-4 Vision on Medical Image Classification -- A Case Study on COVID-19 Dataset	Oct 27, 2023	Diagnosticimage-classification	—Unverified
Embeddings are all you need! Achieving High Performance Medical Image Classification through Training-Free Embedding Analysis	Dec 12, 2024	AllClassification	—Unverified
A Deep Bayesian Convolutional Spiking Neural Network-based CAD system with Uncertainty Quantification for Medical Images Classification	Apr 23, 2025	Deep Learningimage-classification	—Unverified
Imbalanced Classification in Medical Imaging via Regrouping	Oct 21, 2022	Classificationimage-classification	—Unverified
A systematic review of transfer learning based approaches for diabetic retinopathy detection	May 28, 2021	Diabetic Retinopathy Detectionimage-classification	—Unverified
Improving Sample Complexity with Observational Supervision	Mar 25, 2019	image-classificationImage Classification	—Unverified
Embedding Radiomics into Vision Transformers for Multimodal Medical Image Classification	Apr 15, 2025	image-classificationImage Classification	—Unverified
A Novel Momentum-Based Deep Learning Techniques for Medical Image Classification and Segmentation	Aug 11, 2024	Benchmarkingimage-classification	—Unverified
A Novel Global Spatial Attention Mechanism in Convolutional Neural Network for Medical Image Classification	Jul 31, 2020	Binary ClassificationClassification	—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