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 371–380 of 424 papers

Title	Date	Tasks	Status
Enhancing Multimodal Medical Image Classification using Cross-Graph Modal Contrastive Learning	Oct 23, 2024	ClassificationContrastive Learning	CodeCode Available
MIAFEx: An Attention-based Feature Extraction Method for Medical Image Classification	Jan 15, 2025	Classificationimage-classification	CodeCode Available
CECT: Controllable Ensemble CNN and Transformer for COVID-19 Image Classification	Feb 5, 2023	ClassificationCOVID-19 Diagnosis	CodeCode Available
Mind the Gap: Federated Learning Broadens Domain Generalization in Diagnostic AI Models	Oct 1, 2023	DiagnosticDiversity	CodeCode Available
Cats, not CAT scans: a study of dataset similarity in transfer learning for 2D medical image classification	Jul 13, 2021	image-classificationImage Classification	CodeCode Available
ARIA: On the Interaction Between Architectures, Initialization and Aggregation Methods for Federated Visual Classification	Nov 24, 2023	Federated Learningimage-classification	CodeCode Available
Robustly Optimized Deep Feature Decoupling Network for Fatty Liver Diseases Detection	Jun 25, 2024	image-classificationImage Classification	CodeCode Available
Emergent symbolic language based deep medical image classification	Aug 22, 2020	ClassificationDecision Making	CodeCode Available
Embedding Byzantine Fault Tolerance into Federated Learning via Virtual Data-Driven Consistency Scoring Plugin	Nov 15, 2024	Federated Learningimage-classification	CodeCode Available
Addressing Small and Imbalanced Medical Image Datasets Using Generative Models: A Comparative Study of DDPM and PGGANs with Random and Greedy K Sampling	Dec 17, 2024	Denoisingimage-classification	CodeCode Available

Show:10 25 50

← PrevPage 38 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