Dr. Suzanne Tamang is an Assistant Professor at the Stanford University School of Medicine and a Senior Computer Scientist at the Department of Veterans Affairs. She uses her training in biology, computer science, health services research and biomedical informatics to work with interdisciplinary teams of experts on population health problems of public interest. Integral to her research, is the analysis of large and complex population-based datasets, using techniques from natural language processing, machine learning and deep learning. Her expertise spans US and Danish population-based registries, Electronic Medical Records from various vendors, administrative healthcare claims and other types of observational health and demographic data sources in the US and internationally; also, constructing, populating, and applying knowledge-bases for automated reasoning. Dr. Tamang has developed open-source tools for the extraction of health information from unstructured free-text patient notes and licensed machine learning prediction models to Silicon Valley health analytics startups. She is also the faculty mentor for the Stanford community working group Stats for Social Good.
In this session from “Understanding and Eliminating Bias in HSR Methods: Approaches to Anti-racist Research Design, Analysis, and Dissemination,” presenters discuss methods including community-based participatory research as well as the use of big data to improve outcomes.