Diabetic Retinopathy Prediction Using Machine Learning
Diabetic retinopathy is among the notorious complications of diabetes and a leading cause of blindness among adults. Since prevention of vision loss in diabetic retinopathy is possible when the disease is detected early and interventions instituted, screening is highly essential for this disease....
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| Format: | Article |
| Language: | English English |
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INTI International University
2024
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| Online Access: | http://eprints.intimal.edu.my/2095/ http://eprints.intimal.edu.my/2095/2/634 http://eprints.intimal.edu.my/2095/3/joit2024_45b.pdf |
| _version_ | 1848766918713933824 |
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| author | Ravikiran, Y. Usha Sree, R. |
| author_facet | Ravikiran, Y. Usha Sree, R. |
| author_sort | Ravikiran, Y. |
| building | INTI Institutional Repository |
| collection | Online Access |
| description | Diabetic retinopathy is among the notorious complications of diabetes and a leading cause of
blindness among adults. Since prevention of vision loss in diabetic retinopathy is possible when
the disease is detected early and interventions instituted, screening is highly essential for this
disease. However, the process of diagnosing the manual images or studying the images of
retinas is lengthy, and because of the connectivity of these interconnections, they blur in certain
cases. This research aims to provide solutions to the preceding challenges through the
development of a web application that can have the ability to diagnose diabetic retinopathy
based on machine learning methods. Within the framework of a rolling scheme, CNN is utilized
for a group of retinal images when the images can be recognized and diagnosed quickly. The
web application is built in the Flask web application platform deliberately for the purpose of
providing the user a rich experience as they upload retina images and receive feedback whether
there is any abnormality or not. This approach enables doctor to be present in a better position
in the assessment of the general surrounding environment while patients become more
conscious and responsible for their vision. Preparing the data, training the model, validating
and testing it, and integrating it into a web-based platform to use the created model are all
included in this. Additionally, this page explains the significance of the established model for
diabetes retinopathy screening and management. |
| first_indexed | 2025-11-14T11:58:47Z |
| format | Article |
| id | intimal-2095 |
| institution | INTI International University |
| institution_category | Local University |
| language | English English |
| last_indexed | 2025-11-14T11:58:47Z |
| publishDate | 2024 |
| publisher | INTI International University |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | intimal-20952025-07-12T03:52:10Z http://eprints.intimal.edu.my/2095/ Diabetic Retinopathy Prediction Using Machine Learning Ravikiran, Y. Usha Sree, R. QA75 Electronic computers. Computer science RA Public aspects of medicine T Technology (General) TJ Mechanical engineering and machinery Diabetic retinopathy is among the notorious complications of diabetes and a leading cause of blindness among adults. Since prevention of vision loss in diabetic retinopathy is possible when the disease is detected early and interventions instituted, screening is highly essential for this disease. However, the process of diagnosing the manual images or studying the images of retinas is lengthy, and because of the connectivity of these interconnections, they blur in certain cases. This research aims to provide solutions to the preceding challenges through the development of a web application that can have the ability to diagnose diabetic retinopathy based on machine learning methods. Within the framework of a rolling scheme, CNN is utilized for a group of retinal images when the images can be recognized and diagnosed quickly. The web application is built in the Flask web application platform deliberately for the purpose of providing the user a rich experience as they upload retina images and receive feedback whether there is any abnormality or not. This approach enables doctor to be present in a better position in the assessment of the general surrounding environment while patients become more conscious and responsible for their vision. Preparing the data, training the model, validating and testing it, and integrating it into a web-based platform to use the created model are all included in this. Additionally, this page explains the significance of the established model for diabetes retinopathy screening and management. INTI International University 2024-12 Article PeerReviewed text en cc_by_4 http://eprints.intimal.edu.my/2095/2/634 text en cc_by_4 http://eprints.intimal.edu.my/2095/3/joit2024_45b.pdf Ravikiran, Y. and Usha Sree, R. (2024) Diabetic Retinopathy Prediction Using Machine Learning. Journal of Innovation and Technology, 2024 (45). pp. 1-6. ISSN 2805-5179 http://ipublishing.intimal.edu.my/joint.html |
| spellingShingle | QA75 Electronic computers. Computer science RA Public aspects of medicine T Technology (General) TJ Mechanical engineering and machinery Ravikiran, Y. Usha Sree, R. Diabetic Retinopathy Prediction Using Machine Learning |
| title | Diabetic Retinopathy Prediction Using Machine Learning |
| title_full | Diabetic Retinopathy Prediction Using Machine Learning |
| title_fullStr | Diabetic Retinopathy Prediction Using Machine Learning |
| title_full_unstemmed | Diabetic Retinopathy Prediction Using Machine Learning |
| title_short | Diabetic Retinopathy Prediction Using Machine Learning |
| title_sort | diabetic retinopathy prediction using machine learning |
| topic | QA75 Electronic computers. Computer science RA Public aspects of medicine T Technology (General) TJ Mechanical engineering and machinery |
| url | http://eprints.intimal.edu.my/2095/ http://eprints.intimal.edu.my/2095/ http://eprints.intimal.edu.my/2095/2/634 http://eprints.intimal.edu.my/2095/3/joit2024_45b.pdf |