Smart Medical Health Prediction Application Using Data Mining Integrated With Deep Learning for Cataract Detection
Abstract
Cataract is a major cause of avoidable vision loss, and early screening is essential to prevent blindness. This work proposes a smart medical health prediction system that combines data mining with deep learning to automatically detect cataract from ocular images. Preprocessing techniques are used to clean and enhance images, while a convolutional neural network classifies eyes as normal or cataract-affected. The system is designed as an assistive tool to provide fast, low-cost, and reliable screening support, especially in resource-limited settings. Experimental results show good accuracy and sensitivity, demonstrating that the integrated approach improves early detection and supports clinical decision- making in ophthalmology.
Fields of Study & Subjects
Retinal Imaging and Analysis
Artificial Intelligence in Healthcare
Ophthalmology and Visual Health Research
Publication details
- Journal / source
- International Journal on Advanced Computer Theory and Engineering
- Volume
- 15
- Issue
- 1S
- Pages
- 350–360
- Publication date
- 18 January 2026
- Language
- EN