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 11–20 of 424 papers

Title	Date	Tasks	Status	Hype
Expert-Like Reparameterization of Heterogeneous Pyramid Receptive Fields in Efficient CNNs for Fair Medical Image Classification	May 19, 2025	Fairnessimage-classification	—Unverified	0
Improving Generalizability of Kolmogorov-Arnold Networks via Error-Correcting Output Codes	May 9, 2025	Classificationimage-classification	CodeCode Available	0
Adapting a Segmentation Foundation Model for Medical Image Classification	May 9, 2025	Classificationimage-classification	—Unverified	0
V-EfficientNets: Vector-Valued Efficiently Scaled Convolutional Neural Network Models	May 8, 2025	image-classificationImage Classification	CodeCode Available	0
CLOG-CD: Curriculum Learning based on Oscillating Granularity of Class Decomposed Medical Image Classification	May 3, 2025	image-classificationImage Classification	—Unverified	0
A Deep Bayesian Convolutional Spiking Neural Network-based CAD system with Uncertainty Quantification for Medical Images Classification	Apr 23, 2025	Deep Learningimage-classification	—Unverified	0
CheXWorld: Exploring Image World Modeling for Radiograph Representation Learning	Apr 18, 2025	Common Sense Reasoningimage-classification	CodeCode Available	1
Embedding Radiomics into Vision Transformers for Multimodal Medical Image Classification	Apr 15, 2025	image-classificationImage Classification	—Unverified	0
A Hybrid Fully Convolutional CNN-Transformer Model for Inherently Interpretable Medical Image Classification	Apr 11, 2025	image-classificationImage Classification	—Unverified	0
Secure Diagnostics: Adversarial Robustness Meets Clinical Interpretability	Apr 7, 2025	Adversarial AttackAdversarial Robustness	—Unverified	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