Project Title | Validation of Anaphylaxis Using Machine Learning |
Date Posted |
Thursday, October 11, 2018 |
Status |
In progress |
Description |
The goal of this pilot project is to develop a draft framework to use machine learning and natural language processing (NLP) techniques to improve health outcome of interest (HOI) detection algorithms that may later be used in the larger Sentinel Distributed Database. This project has 4 aims:
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Workgroup Leader(s) |
Jennifer Nelson PhD; David Carrell PhD; Kaiser Permanente Washington Health Research Institute, Seattle, WA |
Workgroup Members |
Robert Ball MD, MPH, ScM; Steven Bird PharmD, PhD, MS; Sara Karami PhD, MPH; Danijela Stojanovic PharmD, PhD; Office of Surveillance and Epidemiology, Center for Drug Evaluation and Research, FDA, Silver Spring, MD Yong Ma PhD; Yueqin Zhao PhD; Office of Biostatistics, Center for Drug Evaluation and Research, FDA, Silver Spring, MD David Cronkite MS; Monica Fuji MPH; Jing Zhou PhD; Kaiser Permanente Washington Health Research Institute, Seattle, WA James Floyd MD, MS; University of Washington, Seattle, WA Adi Bejan PhD; Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN Kevin Haynes PharmD, MSCE; HealthCore, Wilmington, DE Brian Hazlehurst PhD; Kaiser Permanente Center for Health Research, Kaiser Permanente Northwest, Portland, OR Adee Kennedy MS, MPH; Judith Maro PhD; Mayura Shinde PhD, MPH; Department of Population Medicine, Harvard Pilgrim Health Care Institute and Harvard Medical School, Boston, MA Susan Gruber PhD, MPH; Putnam Data Sciences, LLC. |
Health Outcome |
anaphylaxis |
Time Period |
July 2018 – December 2019 |
Data Sources |
Sentinel Distributed Database (SDD) |
Related Links |