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 101–110 of 424 papers

Title	Date	Tasks	Status
Beyond Fine-tuning: Classifying High Resolution Mammograms using Function-Preserving Transformations	Jan 20, 2021	Cancer-no cancer per image classificationGPU	—Unverified
Analysis of Explainable Artificial Intelligence Methods on Medical Image Classification	Dec 10, 2022	Decision MakingExplainable artificial intelligence	—Unverified
Recent Advances in Medical Image Classification	Jun 4, 2025	ClassificationExplainable artificial intelligence	—Unverified
Benchmarking MedMNIST dataset on real quantum hardware	Feb 18, 2025	Benchmarkingimage-classification	—Unverified
Aligning Human Knowledge with Visual Concepts Towards Explainable Medical Image Classification	Jun 8, 2024	Decision MakingDiagnostic	—Unverified
Active Globally Explainable Learning for Medical Images via Class Association Embedding and Cyclic Adversarial Generation	Jun 12, 2023	counterfactualExplainable Artificial Intelligence (XAI)	—Unverified
Distant Domain Transfer Learning for Medical Imaging	Dec 10, 2020	ClassificationComputed Tomography (CT)	—Unverified
Distributed Federated Learning-Based Deep Learning Model for Privacy MRI Brain Tumor Detection	Apr 15, 2024	DiagnosticFederated Learning	—Unverified
Covid-19: Automatic detection from X-Ray images utilizing Transfer Learning with Convolutional Neural Networks	Mar 25, 2020	image-classificationImage Classification	—Unverified
A Lightweight Neural Architecture Search Model for Medical Image Classification	May 6, 2024	Deep Learningimage-classification	—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