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Student opportunities
AI-powered retinal imaging and large language model for diabetes care
This project aims to leverage AI-driven retinal imaging to enable early detection and risk stratification of diabetes-related complications, as well as large language model to enable personalised diabetes care.
Supervisor: Associate Professor Lisa Zhuoting Zhu
Email: lisa.zhu@unimelb.edu.au
Suitable for: PhD, Masters, MD, MBBS, Honours
Diabetes affects millions worldwide and is a major contributor to vision loss and systemic complications. AI-driven retinal imaging has demonstrated remarkable potential in detecting early diabetic retinopathy and other microvascular complications.
This project will develop and validate AI algorithms to analyze retinal biomarkers, enabling early intervention and personalized risk prediction. Furthermore, by incorporating large language models (LLMs), the project will explore how AI-driven decision support systems can assist clinicians in providing tailored diabetes management strategies.
The integration of retinal imaging AI and LLMs aims to bridge the gap between diagnostics and individualized care, ultimately improving patient outcomes in diabetes management.