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 411–420 of 424 papers

Title	Date	Tasks	Status
Automatic Acne Object Detection and Acne Severity Grading Using Smartphone Images and Artificial Intelligence	Aug 3, 2022	Acne Severity GradingMedical Image Classification	CodeCode Available
PRECISe : Prototype-Reservation for Explainable Classification under Imbalanced and Scarce-Data Settings	Aug 11, 2024	image-classificationImage Classification	CodeCode Available
Video Capsule Endoscopy Classification using Focal Modulation Guided Convolutional Neural Network	Jun 16, 2022	Inductive LearningMedical Image Classification	CodeCode Available
Preservation of High Frequency Content for Deep Learning-Based Medical Image Classification	May 8, 2022	Diagnosticimage-classification	CodeCode Available
Preserving privacy in domain transfer of medical AI models comes at no performance costs: The integral role of differential privacy	Jun 10, 2023	DiagnosticDomain Generalization	CodeCode Available
Deep Residual Network based Automatic Image Grading for Diabetic Macular Edema	Jul 1, 2018	Fovea Detectionimage-classification	CodeCode Available
Deep Modeling and Optimization of Medical Image Classification	May 29, 2025	AvgClassification	CodeCode Available
PRICURE: Privacy-Preserving Collaborative Inference in a Multi-Party Setting	Feb 19, 2021	Collaborative Inferenceimage-classification	CodeCode Available
Universal Semi-Supervised Learning for Medical Image Classification	Apr 8, 2023	ClassificationDomain Adaptation	CodeCode Available
Advancements in Medical Image Classification through Fine-Tuning Natural Domain Foundation Models	May 26, 2025	Classificationimage-classification	CodeCode Available

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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