Algorithmic Bias and Machine Learning in Health Care
DISTINGUISHED LECTURE SERIES IN DATA SCIENCE
ALGORITHMIC BIAS AND MACHINE LEARNING IN HEALTH CARE
Columbia Mailman School of Public Health
We are pleased to host the Data Science for Public Health Summit at the Columbia Mailman School of Public Health. This year we will have two invited speakers. Dr. Sherri Rose from Stanford will give The Data Science for Public Health Distinguished Lecture via zoom on January 12that 4:00 pm.
Sherri Rose, PhD is a Professor of Health Policy and Co-Director of the Health Policy Data Science Lab at Stanford University. Her research is centered on developing and integrating innovative statistical machine learning approaches to improve human health and health equity. Within health policy, Dr. Rose works on risk adjustment, ethical algorithms in health care, comparative effectiveness, and health program evaluation. Her honors include an NIH Director’s Pioneer Award, NIH Director’s New Innovator Award, and the Mortimer Spiegelman Award, which recognizes the statistician under age 40 who has made the most significant contributions to public health statistics.
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