Analyses of systemic ageing biomarkers related to retina via deep learning
Aims: The purpose of this study is to develop a novel biomarker that predicts biological age using retina, which is the layer of nerve cells lining the back wall inside the eye via Artificial Intelligence (AI), which refers to the simulation of human intelligence in machines that are programmed to think like humans and mimic their actions.
Scientific rationale: The blood vessels in the eye are where the body can observe the blood vessels directly. Many previous studies have shown that abnormal findings in the blood vessels or nerves in the eye are associated with systemic diseases or conditions. Recent advances in AI provide opportunities to further refine this area of research. In this study, we develop an AI system that can predict biological age by analyzing retinal photographs. UK Biobank is an important data for the validation of this AI system.
Project duration: 36months
Public health impact: Findings from this project may provide important information on biological ageing, which may improve our understanding of the complex mechanism involved in disease development or progression, and accelerate the development of prevention or early detection program for the major life-threatening disease. This project will also provide useful information on the generalizability of AI algorithms with the impact of genetically different populations.