Explainable Deep Learning for Referable Diabetic Retinopathy
Bibliographic record
Abstract
Diabetic Retinopathy (DR) is a retinal lesion due to diabetes. Through blood leaks and excess glucose in the blood vessels, pathological lesions including hemorrhages, exudates and microaneurysms (HM, EX, MA) develop in the eye, which may lead to blindness if not timely treated. In this paper, we propose a deep Convolutional Neural Network (CNN) architecture trained to identify Referable Diabetic Retinopathy (RDR) lesions from retinal fundus images. The model uses a pre-trained network with fine-tuned layers, cosine learning rate decay, and warm up. The efficiency of the proposed architecture has been evaluated on eight public datasets. The results show that the proposed architecture obtains state-of-the-art performance using only publicly available datasets. An explainability algorithm was also developed to show the efficiency of the model in detecting RDR signs.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".