AI-Powered Eye Pathology Detection and Recommendation System
Challenge
A healthcare organisation wanted to modernise its eye-care diagnostic workflows, which were manual, time-consuming and fragmented. Clinicians had to review images and data without structured analysis or automation, slowing assessment and creating room for inconsistency. The organisation also lacked a personalised recommendation engine, so it could not efficiently translate diagnostic findings into tailored guidance and product suggestions for each patient, limiting both speed and quality of care.
A healthcare organisation wanted to modernise its eye-care diagnostic workflows, which were manual, time-consuming and fragmented. Clinicians had to review images and data without structured analysis or automation, slowing assessment and creating room for inconsistency. The organisation also lacked a personalised recommendation engine, so it could not efficiently translate diagnostic findings into tailored guidance and product suggestions for each patient, limiting both speed and quality of care.
Solution
INNERLUXES created an AI-assisted eye pathology detection and prescription system that automates manual screening and delivers real-time diagnostic results. Built with Python and Django, AI and ML models, an MVC web application and HTML/CSS/JavaScript on SQLite, it combines computer vision with automated segmentation to analyse eye images and a personalised recommendation engine to suggest suitable products. The platform structures the diagnostic process so clinicians get quick, consistent, data-driven insights.
INNERLUXES created an AI-assisted eye pathology detection and prescription system that automates manual screening and delivers real-time diagnostic results. Built with Python and Django, AI and ML models, an MVC web application and HTML/CSS/JavaScript on SQLite, it combines computer vision with automated segmentation to analyse eye images and a personalised recommendation engine to suggest suitable products. The platform structures the diagnostic process so clinicians get quick, consistent, data-driven insights.
Results
The system replaces slow, manual screening with automated, real-time analysis, giving clinicians faster and more consistent diagnostic results and structured assessments. Automated segmentation and personalised recommendations streamline patient evaluation, helping the organisation make quicker, better-informed decisions and deliver more tailored, efficient eye care.
The system replaces slow, manual screening with automated, real-time analysis, giving clinicians faster and more consistent diagnostic results and structured assessments. Automated segmentation and personalised recommendations streamline patient evaluation, helping the organisation make quicker, better-informed decisions and deliver more tailored, efficient eye care.