On March 11,2025, the Eye Care Center (ECC) at the Faculty of Medicine, University of Colombo, in collaboration with the Institute for Health Policy (IHP), hosted a public education session on World Glaucoma Week. The session was attended by the Dean of the Medical Faculty, Prof. Vajira Dissanayake, senior clinicians and optometry students. The event provided targeted information to its audience on the burden of disease presented by diabetic retinopathy and showcased the potential use of AI for early detection in primary and secondary healthcare settings.
Session Highlights
The event started with a presentation by Professor Madhuwanthi Dissanayake, Director of the ECC and Consultant Eye Surgeon. Prof. Dissanayake referred to glaucoma as a "silent thief of sight," as it generally develops without symptoms, with permanent vision loss if untreated, and is the second leading cause of blindness worldwide. She emphasised the importance of early screening for immediate treatment.
Dr Malinda De Silva, Health Informatics and Telemedicine specialist, then discussed the potential for using AI to screen for signs of glaucoma in primary and secondary healthcare setting, presenting findings from early analysis from the DIAGNOSE-Diabetic Retinopathy project. Dr De Silva detailed how fundus photographs captured by digital fundus cameras can be interpreted in real-time by AI software to detect risk of glaucoma with high accuracy. Dr. De Silva emphasised AI’s potential to enhance diagnostic effectiveness, particularly in resource-limited settings where access to specialists is restricted.
The research team from the Institute for Health Policy then provided a demonstration of the AI-assisted digital retinal camera being used for the DIAGNOSE-Diabetic Retinopathy project, showing how it can analyse retinal scans in real-time to identify signs of referrable glaucoma and diabetic retinopathy.
The demonstration illustrated how AI-assisted devices can reduce human error and close healthcare gaps, especially among underserved communities where specialists are not easily accessible. In rural or remote areas, where the presence of trained ophthalmologists and advanced diagnostic tools is lacking, AI-assisted systems can read retinal scans remotely and provide accurate diagnoses in a timely fashion. By automating retinal image interpretation, AI frees clinicians to focus on other areas of patient care and treatment planning, improving healthcare delivery as a whole.
Participant Engagement
The session had keen interest among the attending students, employees, and faculty members. Participants enthusiastically engaged in the demonstration and discussion, appreciating its potential to improve clinical workflows and facilitate timely intervention even in geographically remote areas. The event was covered by the local media to increase community awareness.
