Machine Learning for Personalized Cancer Screening

Adam Yala is an assistant professor of Computational Precision Health, Statistics and Computer Science at UC Berkeley and UCSF. His research focuses on developing machine learning methods for personalized medicine and translating them into clinical care.  His previous research has focused on two areas: 1) predicting future cancer risk, and 2) designing personalized screening policies. His breast cancer tool, Mirai, has been tested at 43 hospitals from 14 countries. Adam's tools now underly prospective trials, and his research has been featured in the Washington Post, New York Times, and the Boston Globe. Prof Yala obtained his BS, MEng and PhD in Computer Science from MIT where he was a member of MIT Jameel Clinic and MIT CSAIL.