Detection of Multiple Ocular Diseases Using Machine Learning
Aadhitya S
ANN, CNN, Machine Learning, MLP, Ocular diseases
Vision plays an indispensable role in almost every aspect of life. Unfortunately, various ocular diseases can significantly impair vision, leading to reduced quality of life and even blindness if left untreated. Age related Macular degeneration, Glaucoma, Cataract, Hypertensive Retinopathy, and Pathological Myopia are among the most prevalent ocular diseases globally. The integration of machine learning algorithms in ocular disease detection presents a promising avenue for improving early diagnosis and intervention. Convolutional Neural Networks (CNN), Artificial Neural Networks (ANN), Multi-Layer Perceptron (MLP) networks are among the machine learning algorithms that have been analysed in this work. Key metrics like accuracy, loss, sensitivity, ROC, AUC, scalability obtained by training CNN, ANN and MLP models are compared to recommend the highly efficient model. The results showed that CNN has emerged as the best model for ocular disease prediction.
Article Details
Unique Paper ID: 163447

Publication Volume & Issue: Volume 10, Issue 11

Page(s): 1110 - 1115
Article Preview & Download

Share This Article

Join our RMS

Conference Alert

NCSEM 2024

National Conference on Sustainable Engineering and Management - 2024

Last Date: 15th March 2024

Call For Paper

Volume 11 Issue 1

Last Date for paper submitting for Latest Issue is 25 June 2024

About Us enables door in research by providing high quality research articles in open access market.

Send us any query related to your research on

Social Media

Google Verified Reviews