Join the Secondary Data in Aging Interest Group for Machine Learning: An Overview of Fundamentals and Applications, presented by Ruopeng An, PhD.
Born in the 1950s, artificial intelligence (AI) symbolizes the effort to automate intellectual tasks usually performed by humans. Machine Learning is an AI application that provides computer systems the ability to learn and improve from experience without being explicitly programmed automatically. In the recent decade, machine Learning models have been increasingly recognized as an indispensable tool in the field of health sciences, and their applications are rapidly expanding from outbreak prediction to medical imaging and from patient communication to behavioral modification.
This talk provides an high-level overview of the fundamental concepts and applications of machine learning in health sciences and beyond.
The Secondary Data in Aging Interest Group is an interdisciplinary learning collaborative. Focusing on research using secondary data, this group discusses theoretical and methodological issues and research of policy and programs relevant for a person’s life course and aging.
All experience levels, department and university/organization affiliations are invited. This event will take place via Zoom.
About the speaker
Ruopeng An, PhD
Associate Professor, Brown School
Ruopeng An conducts research to assess environmental influences and population-level interventions on weight-related behaviors and outcomes throughout the life course. In particular, his work assesses socioeconomic determinants and policies that impact individuals’ dietary behavior, physical activity, sedentary lifestyle, and adiposity in children, adults of all ages, and people living with a disability.
The goal of his research has been to develop a well-rounded knowledge base and policy recommendations that can inform decision making and the allocation of resources to combat obesity.
Event Sponsors: Harvey A. Friedman Center for Aging at Institute for Public Health