Biography
Lauren Eyler, M.D., M.P.H., is a general surgery resident at UCSF. During the research years of her residency, she is currently pursuing a Ph.D. in Biostatistics at UC Berkeley. She previously received her B.S. from Yale University in Molecular, Cellular, and Developmental Biology, her M.P.H. from UC Berkeley, and her M.D. from UCSF. Her research focuses on developing novel machine learning algorithms to help build surgical systems and improve health equity in low- and middle-income countries.
Education
Yale University - B.S., Molecular, Cellular, & Developmental Biology - 2011
University of California, Berkeley - M.P.H., Interdisciplinary Program - 2015
University of California, San Francisco School of Medicine - M.D. - 2016
University of California San Francisco Medical Center - General Surgery Intern - 2016-2017
University of California San Francisco Medical Center - General Surgery Resident - 2017-present
UCSF General Surgery Residency Program
Clinical Interests
Improving surgical care in low-resource settings
Foreign Languages Spoken
Spanish (fluent), French (basic)
Kisitu DK, Eyler LE, Kajja I, Waiswa G, Beyeza T, Feldhaus I, Juillard C, Dicker RA. A pilot orthopedic trauma registry to assess needs and disparities in Ugandan district hospitals. 11th Academic Surgical Congress. Jacksonville, Florida. February 2, 2016. Oral Presentation.
In the News
Grants and Funding
UC Berkeley/NIH Biomedical Big Data Fellowship
Research Narrative
Lauren is interested in developing novel machine learning algorithms to help build surgical systems and improve health equity in low- and middle-income countries (LMICs).
She previously wrote a k-medoids clustering based algorithm to define simple, population-specific metrics of economic status for LMICs based on Demographic and Health Surveys (DHS) data. These EconomicClusters models may be used for health disparities research in settings where traditional metrics, which are based on lengthy questionnaires, are not feasible to assess. She developed an R package available on Github and R Shiny app so that other researchers may develop EconomicClusters models for any country with DHS data.
She is currently working on a statistical algorithm to minimize the computational capacity required to predict hypotensive events from pulse oximetry waveform data.
Research Interests
Global Surgery
Health Equity
Biostatistics
Machine Learning