Development of an automated web-based screening system for eye diseases
Half of all major eye diseases, such as glaucoma, age-related macular degeneration and diabetic retinopathy, are undetected in Australia. Retinal imaging is a powerful screening mechanism to identify people with eye diseases. However, the interpretation of retinal images is highly dependent on clinical experts. This limits the efficiency, accessibility and affordability of screening programs. We have developed a web-based system that incorporates an artificial intelligence-based automatic grading algorithm with proven efficiency and accuracy. In this proposal we will further customise the system based on end-user need to build, validate and translate these technologies into an efficient screening system.
Our system will deliver a technology-driven and user-friendly screening solution to identify people with chronic eye diseases such as glaucoma, diabetic retinopathy and age-related macular degeneration, which together account for >50% of blindness in Australia. The platform will be less reliant on retinal professionals and thus screening can be performed at optometry or diabetes clinics. This will improve the accessibility of patients, reducing waiting times for end-users and therefore optimising the potential to reduce vision loss. The cost to governments and insurance providers will also be reduced when the referrals to ophthalmologists will be more targeted.
Dr Andreas Muller
Dr Stuart Keel, Research Feloow
Dr William Yan PhD student
Ms Pei Ying Lee, Research Optometrist
www.eyegrader.com, a web-based solution for screening of eye diseases
Healgoo Inc, Guangzhou, China
Bupa Health Foundation
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