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 211–220 of 424 papers

Title	Date	Tasks	Status
Highly Efficient Representation and Active Learning Framework and Its Application to Imbalanced Medical Image Classification	Feb 25, 2021	Active LearningClassification	—Unverified
Unsupervised Feature Learning with K-means and An Ensemble of Deep Convolutional Neural Networks for Medical Image Classification	Jun 7, 2019	ClusteringDeep Learning	—Unverified
HMIC: Hierarchical Medical Image Classification, A Deep Learning Approach	Jun 12, 2020	ClassificationDeep Learning	—Unverified
Adapting a Segmentation Foundation Model for Medical Image Classification	May 9, 2025	Classificationimage-classification	—Unverified
Combining Similarity and Adversarial Learning to Generate Visual Explanation: Application to Medical Image Classification	Dec 14, 2020	General Classificationimage-classification	—Unverified
How does self-supervised pretraining improve robustness against noisy labels across various medical image classification datasets?	Jan 15, 2024	Contrastive Learningimage-classification	—Unverified
How much data is needed to train a medical image deep learning system to achieve necessary high accuracy?	Nov 19, 2015	ClassificationComputed Tomography (CT)	—Unverified
How Transferable Are Self-supervised Features in Medical Image Classification Tasks?	Aug 23, 2021	Classificationimage-classification	—Unverified
Hybrid Deep Learning Framework for Classification of Kidney CT Images: Diagnosis of Stones, Cysts, and Tumors	Feb 5, 2025	Deep Learningimage-classification	—Unverified
Cluster-Guided Semi-Supervised Domain Adaptation for Imbalanced Medical Image Classification	Mar 2, 2023	ClusteringDomain Adaptation	—Unverified

Show:10 25 50

← PrevPage 22 of 43Next →

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