Large Language Models (LLMs) are powerful tools for text processing, holding immense potential in health applications. However, they lack a specific medical focus. How can we optimise their accuracy for clinical tasks and curb misinformation phenomena such as hallucinations? Attention has also been drawn to ethical concerns, given their high-stakes applications in health. Much clarity is needed to resolve such issues beyond the ongoing discussion and development of guidelines and regulations. 

Join Dr Daniel Lim and Assoc Prof Liu Nan as they highlight gaps and delve into the clinical applications, technicalities, and ethical considerations surrounding the safe and effective use of LLMs and Generative AI in health.

Dr Daniel Lim Yan Zheng is a Gastroenterology Senior Resident of SingHealth Residency and Data Science Fellow in the Data Science and Artificial Intelligence Lab (DSAIL) at Singapore General Hospital (SGH). He is dual qualified as a Master of Technology and a Data Science Fellow with DSAIL, and worked on large data from electronic health records, natural language models, and medical images. He published in multiple high impact journals (Diabetes Care, British Journal of Anaesthesia, Journal of Gastroenterology and Hepatology) on the applications of Large Language Models in healthcare.

Assoc Prof Liu Nan is the Director at Duke-NUS AI + Medical Sciences Initiative (DAISI), and an Associate Professor in the Centre for Quantitative Medicine at Duke-NUS Medical School. His research focuses on AI and Machine Learning with applications to Medical Informatics, Health Services Research, Emergency and Critical Care, Cardiology, and Health Innovation. Assoc Prof Liu Nan is a recipient of multiple research grants from the National Medical Research Council, National Health Innovation Centre, and National Research Foundation, and recognised as one of the World’s Top 2% Scientists by Stanford University and Elsevier. He also served as an Editor for many prestigious peer-reviewed journals, such as npj Digital Medicine and PLOS Medicine.

Assoc Prof Daniel Ting is the Director of the AI Office in SingHealth, and the Head of AI and Digital Health at Singapore Eye Research Institute (SERI). He is an Associate Professor at Duke-NUS Medical School and Stanford University. Assoc Prof Ting published over 250 peer-reviewed publications in high-impact journals, such as JAMA, NEJM, Lancet, Nature Medicine, and serves in American Academy of Ophthalmology, STARD-AI, QUADAS-AI and DECIDE-AI as executive committee. He is ranked the Top 100 Ophthalmologists Power list by the Ophthalmologists and ranked Top 100 Clinical Research (0.001%) in the World’s Top 2% Scientists by Stanford University in 2022 and 2023. He is also ranked 1st for Deep Learning AI Research scientist in the world across all domains (>55K researchers) by the ExpertScape from 2010 to 2021.

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