Hosted by the GPH Department of Biostatistics and NYU Grossman Division of Biostatistics
As risk prediction models become embedded in healthcare practice, real-world scenarios expose the intertwined nature of data collection and analytic model development. Dr. Rumi Chunara, Associate Professor of Biostatistics at GPH, will first illustrate this based on the problem of guaranteeing performance and fairness for prediction in unseen environments. She will next show the importance of understanding the data generating process for prediction models via findings from a study of mortality prediction in data from 179 hospitals across the United States. Third, she will share their new NIH training program on Data Science for Social Determinants, and why such training is also is an important effort towards improving data and machine learning in health applications.
About the Speaker:
Rumi Chunara, PhD is an Associate Professor at New York University, jointly appointed at the School of Global Public Health (in Biostatistics/Epidemiology) and the Tandon School of Engineering (in Computer Science) and Director of the Center for Health Data Science. Her PhD is from the Harvard-MIT Division of Health Sciences and Technology and her BSc is from Caltech. Her research group focuses on developing computational and statistical approaches for acquiring, integrating and using data to improve population and public health. She is an MIT TR35, NSF Career, Bill & Melinda Gates Foundation Grand Challenges, Facebook Research and Max Planck Sabbatical award winner.