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International Journal of Science, Strategic Management and Technology

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DIABETIC RETINOPATHY DETECTION

AUTHORS:
Sagar Chakre
Manthan Ronghe
Attadip Somkuwar
Ritik Bansod
Mentor
Asst. Prof.Priya Kamble
Affiliation
Dept. of Industrial IoT, Priyadarshini College of Engineering. Nagpur, Maharashtra, India
DOI: 10.55041/ijsmt.v2i4.272
CC BY 4.0 License:
This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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Abstract

Diabetic retinopathy is an eye disease caused by diabetes that can lead to blindness if not detected early. This project proposes an automated system for detecting diabetic retinopathy using deep learning techniques. The system analyses retinal images and classifies them into different stages of the disease. The proposed method helps doctors in early diagnosis and reduces manual effort.

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PUBLICATION DETAILS
Review Type:
Double-Blind Peer Review
License:
CC BY-NC 4.0
Volume/Issue:
Volume 02, Issue 04
Review Rounds:
2
Article Type:
Research Article
Publication Date:
Apr 13 2026
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Chakre, S., Ronghe, M., Somkuwar, A. & Bansod, R. (2026). Diabetic Retinopathy Detection. International Journal of Science, Strategic Management and Technology, 02(04). https://doi.org/10.55041/ijsmt.v2i4.272

Chakre, Sagar, et al.. "Diabetic Retinopathy Detection." International Journal of Science, Strategic Management and Technology, vol. 02, no. 04, 2026, pp. . doi:https://doi.org/10.55041/ijsmt.v2i4.272.

Chakre, Sagar,Manthan Ronghe,Attadip Somkuwar, and Ritik Bansod. "Diabetic Retinopathy Detection." International Journal of Science, Strategic Management and Technology 02, no. 04 (2026). https://doi.org/https://doi.org/10.55041/ijsmt.v2i4.272.

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Ethics and Compliance
✓ All ethical standards met
This article has undergone plagiarism screening and double-blind peer review. Editorial policies have been followed. Authors retain copyright under CC BY-NC 4.0 license. The research complies with ethical standards and institutional guidelines.
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