Detection and Analysis of Diabetic Retinopathy Using Machine Learning

DOI

10.2991/978-94-6463-662-8_22How to use a DOI?

Keywords

Retinopathy; Diabetic Retinopathy; Convolution Neural Networks

Abstract

Diabetic retinopathy, is the most prevalent adverse impact of diabetes mellitus. It causes retinal lesions that impede vision. Failure to detect it in time may lead to blindness. Diagnosing and treating DR early can significantly reduce the risk of vision loss. Non-Proliferative Diabetic Retinopathy and Proliferative Diabetic Retinopathy are the two primary stages of DR. The manual diagnosis of DR retina fundus images by ophthalmologists is time-consuming, slow, costly, and capable of inaccuracy in comparison to computer-aided diagnosis technologies. This Paper focuses on decision about the presence of disease by applying Convolution Neural Networks (CNN) technique. The implementation is written in Python.

Copyright

© 2025 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - G. Amjad Khan
AU  - M. Madhusudhan Reddy
AU  - R. Sudheer Babu
AU  - K. Lakshmi Devi
PY  - 2025
DA  - 2025/03/17
TI  - Detection and Analysis of Diabetic Retinopathy Using Machine Learning
BT  - Proceedings of the International Conference on Advanced Materials, Manufacturing and Sustainable Development (ICAMMSD 2024)
PB  - Atlantis Press
SP  - 274
EP  - 279
SN  - 2352-5401
UR  - https://doi.org/10.2991/978-94-6463-662-8_22
DO  - 10.2991/978-94-6463-662-8_22
ID  - Khan2025
ER  -