12/15/2025
https://youtu.be/dkie7E3VnoA TOWN HALL VIDEO - User-Friendly Natural Language Processing (NLP) of Free-text Clinical Notes at UCSF: EMERSE and cTAKES. Featuring: William Brown III Ph.D., DrPH, MA , UCSF, and Shivani Meta MPH, UCSF
GOALS of the Workshop
• Learn about NLP tools for research
• Be introduced to user-friendly NLP tools available at UCSF: EMERSE and cTAKES
• Hear about “Use Cases” of NLP for Social Determinants of Health, Diabetes, and Opioid Research
• Help get access to these tools by attending this seminar
• Discuss and get your NLP questions answered
SCHEDULE
Hour 1 - Overview of NLP tools at UCSF. Part 1 https://youtu.be/dkie7E3VnoA
Hour 2 - "Use Case" presentations. Part 2
https://youtu.be/rEvw0zd6T9I
Hour 3 - Access Walk Through, Discussion, and Questions. Part 3 https://youtu.be/LhvgNM3zkkE
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William Brown III, Ph.D., DrPH, MA, Dr. Brown is an Assistant Professor of Medicine & Epidemiology and Biostatistics, Co-Directorship of the CAPS Methods Core, Founding Director of the Clinical and Observational Data Excellence (CODE) Lab code.ucsf.edu, Director of Diversity Equity and Inclusion of the Bakar Computational Health Science Institute, Co-Director of the Data Science Training to Advance Behavioral and Social Science Expertise (DaTABASE) for Health Disparities Research, Associate Director for the Research Coordination and Data management Unit, Research Coordinating Center to Reduce Disparities in Multiple Chronic Diseases (RCC RD-MCD), and Implementation Science Lead for the Center for Digital Health Innovation. He is also on the Board of Directors for the American Medical Informatics Association and the Vice-Chair of its 2022 conference.
Dr. Brown specializes in developing and implementing biomedical informatics-based methods, tools, and interventions (Big Data, mHealth, SMS/text messaging, Natural Language Processing (NLP), Machine Learning (ML), and Federal Data Standards [FHIR, OMOP, UMLS, etc.]) as applied to clinical and behavioral health disparities research, with underserved communities. Using community-based participatory research principles and informatics, he works to reduce chronic illness (i.e., HIV, diabetes) and health disparities, particularly among vulnerable populations (i.e., African-Americans, Latinos, youth, and LGBT). He has been a PI, Co-I, research scientist, or consultant for many HIV, Diabetes, Opioids grants for NIH, AHRQ, Ford Foundation, NSF, and CDC. Dr. Brown’s CODE Lab leverages big data, data standards, mHealth, social media, data harmonization and integration, NLP, ML, and data visualization to improve health. He implements tools to collect data in real-time, integrate data sources, improve the quality of provider-patient communication, and the responsiveness of the clinical care delivery system to the needs of individual patients. Dr. Brown is a committed instructor and mentor, co-directs the T32 DaTABASE program, directs courses on informatics tools and health disparities research, and conducts one-on-one mentoring of scholars at all levels.
Shivani Mehta, MPH Shivani is a Ph.D. student in the Department of Epidemiology and Biostatistics and a member of Dr. Brown’s CODE Lab. She has an MPH from Brown School of Public Health in applied epidemiology and biostatistics. She specializes in applying predictive models and machine learning technology in clinical research informatics and was the associate research scientist at a biotech consulting firm. She has expertise in statistical programming in R, systematic literature reviews, Bayesian methods, patient-centered outcomes research, and meta-analysis.