Stage Aware Diagnosis of Diabetic Retinopathy via Ordinal Regression

• URL: http://arxiv.org/abs/2511.14398v1
• Date: Tue, 18 Nov 2025 12:02:50 GMT
• Title: Stage Aware Diagnosis of Diabetic Retinopathy via Ordinal Regression
• Authors: Saksham Kumar, D Sridhar Aditya, T Likhil Kumar, Thulasi Bikku, Srinivasarao Thota, Chandan Kumar,
• Abstract summary: The work introduces a state-of-the-art Ordinal Regression-based DR Detection framework that uses the APTOS 2019 fundus image dataset.<n>A combination of preprocessing methods was used to isolate the most relevant features for DR classification.<n>Our Ordinal Regression approach attained a QWK score of 0.8992, setting a new benchmark on the APTOS dataset.
• Score: 2.5755043179316623
• License: http://creativecommons.org/licenses/by-nc-nd/4.0/
• Abstract: Diabetic Retinopathy (DR) has emerged as a major cause of preventable blindness in recent times. With timely screening and intervention, the condition can be prevented from causing irreversible damage. The work introduces a state-of-the-art Ordinal Regression-based DR Detection framework that uses the APTOS-2019 fundus image dataset. A widely accepted combination of preprocessing methods: Green Channel (GC) Extraction, Noise Masking, and CLAHE, was used to isolate the most relevant features for DR classification. Model performance was evaluated using the Quadratic Weighted Kappa, with a focus on agreement between results and clinical grading. Our Ordinal Regression approach attained a QWK score of 0.8992, setting a new benchmark on the APTOS dataset.

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