Detection of Multiple Ocular Diseases Using Machine Learning

Detection of Multiple Ocular Diseases Using Machine Learning
Author(s):
Aadhitya S
Keywords:
ANN, CNN, Machine Learning, MLP, Ocular diseases
Abstract
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
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