Natural language processing (NLP) techniques have been applied to investigate drug interactions and adverse drug events, but have limited applications to support dietary supplements research. The use of dietary supplements in the U.S. has dramatically increased in recent years, but our ability is currently limited to identify the potential interactions between dietary supplements and medications. Much related information is embedded in the unstructured data, such as biomedical literature and clinical notes. This talk will introduce the use of NLP technique to support dietary supplement research. Specifically, we will demonstrate NLP applications in discovering drug-supplement interactions from biomedical literature and identifying supplement use status in clinical notes.
After participating in this activity, the learner should be better able to:
• Identify needs and challenges of NLP for dietary supplement research
• Understand NLP tools for discovering drug-supplement interactions
• Discuss use cases of text mining techniques in clinical notes of EHR
Rui Zhang, PhD
Department of Pharmaceutical Care & Health Systems and Institute for Health Informatics
University of Minnesota
Dr. Rui Zhang is an Assistant Professor of Department of Pharmaceutical Care & Health Systems and Institute for Health Informatics at the University of Minnesota. His research interests include the secondary analysis of electronic health record (EHR) big data for improving quality of patient care as well as discovery of pharmacovigilance knowledge through mining biomedical literature. One of his current research projects focuses on developing an informatics framework to discover drug-supplement interactions.