Improved early diagnosis of eye diseases by integration of retinal photography and artificial intelligence to build an opportunistic screening service in metro, regional and remote primary care settings

Summary This study is to understand the needs, develop the prototype and evaluate the usability of a AI-based Do-it-Yourself(DIY) fundus image system, in real-world clinical setting of GP and endocrinology clinics and Aboriginal Medical Services.

Project Details

Funded by NHMRC Partnership Grant, this project will based on Professor Mingguang He’s current AI-based fundus image diagnosis system, further develop a do-it-yourself (DIY) screening system that is less dependent on technicians for image acquisition, and less dependent on eye care professionals in the interpretation of clinical images. The aim of the study is to understand the needs, develop the prototype and evaluate the usability of this DIY system, in real-world clinical setting of GP and endocrinology clinics and Aboriginal Medical Services. This DIY screening system is anticipated to allow non-eye professionals to perform eye disease screening that would improve acceptability, accuracy, accessibility and cost-efficiency of eye care delivery.

This project is conducted in Centre for Eye Research Australia, Ophthalmic Epidemiology Unit. It will engage with different partners and collaborators from Diabetes departments in hospitals, GP clinics and Aboriginal Medical Services.