Thinking “deep” to advance machine learning in HEOR: an interview with Vivek Rudrapatna

Following the session at ISPOR—The Professional Society for Health Economics and Outcomes Research's (NJ, USA) Virtual ISPOR Europe 2021 (November 30–December 3), Vivek Rudrapatna, Assistant Professor of Medicine at the University of California, San Francisco (CA, USA), discusses how to use techniques such as natural language processing (NLP) to accelerate the abilities of machine learning (ML) in health economics and outcomes research (HEOR), alongside real-world evidence (RWE) studies. Please could you introduce yourself, your organization(s) and provide a brief summary of your career to date? My name is Vivek Rudrapatna. I’m a physician-scientist and an assistant professor at the University...