Chief Supervisor

Prof. HE Mingguang

Project Title

Synopsis

The increasing demand for ophthalmic care driven by population aging, the rising prevalence of chronic diseases, and advancements in diagnostic technologies, is straining current healthcare systems with clinician shortages, rising costs, and long waiting times. The integration of artificial intelligence (AI) and robotics presents an opportunity to automate ophthalmic examinations and optimize clinical workflows. While AI algorithms such as large language models (LLMs) have shown strong performance in disease grading and medical information interpretation, their integration into robotic systems for physical interaction remains limited. In ophthalmology, such systems have the potential to autonomously conduct examinations, provide follow-up plans, and engage patients, but require rigorous experimental and real-world validation. To address this gap, we will develop and validate an autonomous robotic system within a simulated virtual ophthalmic clinic environment. Performance will then be assessed through simulated task completion, navigation, and question-answering, followed by preclinical testing with healthy volunteers and clinical validation. The findings will provide critical insights into the clinical deployment of AI-driven robotic systems and their potential to enhance ophthalmic clinical workflows.