Using Machine Learning-based Medical Image Analysis to Identify Aging-related Disease

Using Machine Learning-based Medical Image Analysis to Identify Aging-related Disease
Community Collaboration
Hong Kong Eye Hospital
Sun Yat-sen University Hospital (Zhongshan)
Professor Details

Prof Hao Chen

PhD in Computer Science and Engineering

Assistant Professor
Co-Director of Center for Evolution and Health
Associate Director of Center for Medical Imaging and Analysis

Normal Content
Rich Text block

Dr Hao Chen is an Assistant Professor at the Department of Computer Science and Engineering with great expertise in industrial research, his recent research focuses on AI for medical image analysis. AI refers to the technology that mimics human intelligence and teach computer machines how to analyse the details, and medical image analysis uses data from medical machines to locate the disease and the analysis of disease.

Dr Chen’s research encompasses aspects of aging related diseases such as Alzheimer’s, and Parkinson’s Disease with a focus on age-related macular degeneration (AMD). He and his team have been trying to develop four different measurements of disease from the medical images, namely classification, grading, progression, and quantification. The first one is classification; they try to analyse ophthalmology image they took from the machines and identify whether there is disease. Then they move on with the grading where they try and grade the level of the disease, as in the seriousness of the disease and if it requires treatment immediately. Next stage will be to try to predict the progression of the disease, whether the patient has been doing better. The fourth one is to quantify measurement, i.e., map out the volume, size, or morphological feature of the tumour.

Besides the measurement of diseases, Dr Chen’s research on medical image analysis also entails biomarkers for aging-related disease. Identifying biomarkers with ideal accuracy is not an easy task, but as doctors are increasingly relying on biomarkers, there has been a drastic increase in demand for medical image analysis services. Dr Chen believes humans and machines can work collaboratively. Human has an edge on understanding how the patients are feeling and summarizing various symptoms to get to the final diagnosis, while the computer mines high dimensional data and deriving meaningful features which could help navigate treatment strategy.

With rich experience in collaborating with hospitals in the Greater Bay Area such as Hong Kong Eye Hospital, Sun Yat-sen University Hospital in Zhongshan, Dr Chen has been actively working on developing data analysis tools. Besides aging related disease, he is also looking to study the relationship between aging conditions and symptoms from medical image or clinical data with a particular interest in imaging of retinal blood vessels.


Rich Text block