Dr. Yanshan Wang
Dept. of Health Informatics Management, University of Pittsburgh
Abstract: The widespread adoption of Electronic Health Records (EHRs) has enabled the use of clinical data for clinical research and practice. Since a significant portion of relevant patient information is embedded in clinical narratives, natural language processing (NLP) techniques such as information extraction have become critical for using EHRs in clinical research. Meanwhile, encoding entire EHR data in a patient representation has shown promising results in predictive modeling, and could help clinical decision making and facilitate translational research. This talk will feature clinical NLP methodologies and applications, and discuss why learning better representations from EHRs is crucial for clinical and translational research.
Biosketch: Dr. Yanshan Wang is an Assistant Professor and Vice Chair of research with a primary appointment in the Department of Health Information Management, School of Health and Rehabilitation Sciences, and a secondary appointment in the Intelligent Systems Program, School of Computing and Information, at the University of Pittsburgh. His research interests focus on artificial intelligence (AI), natural language processing (NLP), and machine learning methodologies and applications in health care. His research goal is to leverage different dimensions of data and data-driven computational approaches to meet the needs of clinicians, researchers, and patients. He joined Pitt in June 2021 from the Mayo Clinic where he still holds an adjunct Assistant Professor position.