29th July 2026 (Wednesday at 2:00 pm - 3:00 pm)

Abstract:

Alongside developments in sophisticated health data platforms, real-world evidence generated from large-scale routinely collected medical data is increasingly recognised by regulatory authorities worldwide to inform practice and policy. Applications of artificial intelligence in healthcare have also become a key frontier in medical research. Atrial fibrillation affects over 50 million people worldwide, with annual medical costs exceeding 60 billion USD. Long-term oral anticoagulation is essential for stroke prevention in these patients, but inevitably increases the risks of gastrointestinal and intracranial bleeding, especially among elderly and Asians predisposed to bleeding. Important questions remain regarding how to minimise stroke and bleeding risks in these patients, such as antithrombotic regimens following percutaneous coronary intervention and optimal gastroprotective strategies. Traditional risk scores seldom incorporate dynamic and multimodal patient data, and clinical decision support tools based on personalised risk prediction remain limited. Harnessing healthcare big data and artificial intelligence may help address these challenges and beyond.

Biography:

Dr Vincent Yan is a pharmacist with expertise in pharmacoepidemiology research. His research focuses on investigating the safety, effectiveness, cost-effectiveness, patient preferences and utilisation trends of medications, in the areas of cardiovascular medicine, infectious disease and mental health, using multinational healthcare big data. His research interests also include the use of artificial intelligence for clinical risk prediction. His work has been cited by relevant local and national guidelines, such as the Guidance Notes published by the Centre for Health Protection of the HKSAR and the Government of Canada’s Guidance on the use of COVID-19 vaccines, informing practice and policy.

Seminar Room 3, G/F Laboratory Block,
Faculty of Medicine Building, LKS Faculty of Medicine,
The University of Hong Kong,
21 Sassoon Road, Pokfulam, Hong Kong

For enquiries, please contact Ms Yvonne Lee (vonlee@hku.hk)

All are welcome