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....
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English English |
| Published: |
INTI International University
2024
|
| Subjects: | |
| 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 |
| Summary: | 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. |
|---|