Ph.D., Post Doctorate Fellow, UCSF
Nadav Rappoport is currently a post-doctorate scholar at the Bakar Computational Health Sciences Institute, UCSF, in the lab of Prof. Noah Zaitlen. His research expertise lies in machine learning, big biomedical data, Electronic Health Records analysis as well as in molecular and population genetics for improving healthcare and advance precision medicine. In addition, he was nominated as a Clore Foundation’s scholar in 2014. Prior to his position in Prof. Zaitlen’s lab, he pursued 2 years in Prof. Atul Butte lab in UCSF where he did his first steps in the world of clinical research. Nadav graduated from the Hebrew University of Jerusalem in 2015 where he used big data analysis and machine learning methods to predict proteins’ functions integrating big datasets covering 10 million proteins (ProtoNet). Among his recent publications is the identification of genomic variations associated with preterm birth and redefinition of population-specific reference ranges for laboratory tests.
AI and Data Science Showcase: UCSF
The University of California, San Francisco (UCSF) is a leading university dedicated to promoting health worldwide through advanced biomedical research, graduate-level education in the life sciences and health professions, and excellence in patient care.
AI For Multi Sites EHR Systems
Albeit hemorrhage during surgery may be life threatening, there is no standard way to estimate patient’s risk. We trained ML models to predict hemorrhage risk using clinical features usually available at pre-operation time using multi sites analysis.