I lead the Care Health and Reasoning Machines lab to advance machine learning methods in clinical data science. Our lab focuses on improving clinical prediction in internal medicine and critical care settings, with applications in opioid abuse, sepsis, and COVID-19. We develop longitudinal models to analyze electronic health records as their collection mechanisms necessitate advanced analytics for appropriate use and interpretation.
Our lab advances improving and validating risk scores, individualizing treatment recommendations, and promoting analytics-based medicine. My work on survival models from observational, longitudinal data have been included in leading machine learning and medical informatics publications from Neural Information Processing Systems (NeurIPS), the Association for the Advancement of Artificial Intelligence, the American Medical Informatics Association, and the Journal of the American Medical Association. I also review manuscripts across machine learning and clinical venues with top reviewer awards at NeurIPS and the Annals of Internal Medicine.
Related Scientific Focus Areas
Biomedical Engineering and Biophysics
Social and Behavioral Sciences
This page was last updated on Friday, August 25, 2023