vit - diabetic - retinopathy - classification Open - Source Model: Precisely Aid in the Classification and Evaluation of Diabetic Retinopathy

Vit Diabetic Retinopathy Classification

Developed by Kontawat

A diabetic retinopathy classification model based on the Vision Transformer (ViT) architecture, achieving 72.87% accuracy on the evaluation set

Image Classification

Transformers

Open Source License:Apache-2.0 #Diabetic Retinopathy Classification #Medical Image Analysis #ViT Vision Model

Downloads 197

Release Time : 2/24/2023

Model Overview

This model is used to automatically classify the severity of diabetic retinopathy from fundus images, aiding medical diagnosis

Model Features

High Accuracy

Achieves 72.87% classification accuracy on the evaluation set

ViT-Based Architecture

Utilizes the advanced Vision Transformer architecture for processing medical images

Medical Assistance

Assists doctors in early screening of diabetic retinopathy

Model Capabilities

Fundus Image Analysis

Diabetic Retinopathy Grading

Medical Image Classification

Use Cases

Medical Diagnosis

Retinopathy Screening

Automatically analyzes fundus photos and determines the severity of lesions

72.87% evaluation accuracy

Telemedicine

Provides preliminary diagnostic support in areas with limited medical resources

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.5645	0.94	100	0.7731	0.7239
0.3971	1.89	200	0.8123	0.7038
0.3239	2.83	300	0.8204	0.7239
0.2178	3.77	400	0.9085	0.7204
0.18	4.72	500	1.0284	0.7310
0.0501	5.66	600	1.0460	0.7287

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Vit Diabetic Retinopathy Classification

Model Overview

Model Features

Model Capabilities

Use Cases

🚀 vit-diabetic-retinopathy-classification

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📚 Documentation

Model description

Intended uses & limitations

Training and evaluation data

🔧 Technical Details

Training procedure

Training hyperparameters

Training results

Framework versions

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