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metadata
language: en
license: mit
tags:
  - fundus
  - diabetic retinopathy
  - classification
datasets:
  - APTOS
  - EYEPACS
  - IDRID
  - DDR
library: timm
model-index:
  - name: efficientnet_b2
    results:
      - task:
          type: image-classification
        dataset:
          name: EYEPACS
          type: EYEPACS
        metrics:
          - type: kappa
            value: 0.7577868700027466
            name: Quadratic Kappa
      - task:
          type: image-classification
        dataset:
          name: IDRID
          type: IDRID
        metrics:
          - type: kappa
            value: 0.7042314410209656
            name: Quadratic Kappa
      - task:
          type: image-classification
        dataset:
          name: DDR
          type: DDR
        metrics:
          - type: kappa
            value: 0.7354801893234253
            name: Quadratic Kappa

Fundus DR Grading

Rye PyTorch Lightning

Description

This project aims to evaluate the performance of different models for the classification of diabetic retinopathy (DR) in fundus images. The reported perfomance metrics are not always consistent in the literature. Our goal is to provide a fair comparison between different models using the same datasets and evaluation protocol.