The Next Generation of AI and Data Science in Computational Health

Abstract: With the revolution of machine learning technologies in recent years, AI and data science are holding greater promise in understanding diseases and improving quality of care. Computational health is such a research area aiming at developing computational methodologies for deriving insights from various biomedical data. Currently the research in computational health has been mostly siloed, with different communities focusing on analyzing different types of data. However, human health has its own ecosystem with information from all aspects including genome, phenome and exposome. We need to integrate the insights from all of them to have more holistic understandings of diseases. In this talk, I will present the research from my lab health in recent years on building machine learning models for analyzing different types of data involved in different levels of human life science, and the need for transitioning from conventional focused-community based strategy to a holistic full-stack regime for the next-generation health AI/data science research.

About the speaker: Fei Wang is a Professor in Division of Health Informatics, Department of Population Health Sciences, Weill Cornell Medicine (WCM), Cornell University. He is also the founding director of the WCM institute of AI for Digital Health (AIDH).