Overview
I study the meaningful use of Electronic Health Records data. My research interests sit at the intersection of biostatistics, biomedical informatics, machine learning and epidemiology. I collaborate with researchers both locally at Duke as well as nationally. I am interested in speaking with any students, methodologists or collaborators interested in EHR data.
Please find more information at: https://biostat.duke.edu/goldstein-lab
Please find more information at: https://biostat.duke.edu/goldstein-lab
Current Duke Appointments & Affiliations
Professor of Biostatistics & Bioinformatics
·
2023 - Present
Biostatistics & Bioinformatics, Division of Translational Biomedical,
Biostatistics & Bioinformatics
Associate Professor in Pediatrics
·
2020 - Present
Pediatrics, Children's Health Discovery Institute,
Pediatrics
Professor in Population Health Sciences
·
2023 - Present
Population Health Sciences,
Basic Science Departments
Member in the Duke Clinical Research Institute
·
2014 - Present
Duke Clinical Research Institute,
Institutes and Centers
Recent Scholarly Works
Building a Global Research Network for Fair, Accountable, Interpretable, and Responsible AI in Emergency Care: Protocol for a FAIR-EC Study.
Journal article JMIR Res Protoc · August 4, 2026 BACKGROUND: The current landscape of emergency care (EC) is marked by high demand, leading to issues such as emergency department boarding, overcrowding, and subsequent delays that impact the quality and safety of patient care. Integrating data science int ... Full text Link to item CiteDesign and Rationale of the pERSonalized cardIovascuLar dIsease prEvention, treatmeNt, and CarE (RESILIENCE) study.
Journal article Contemp Clin Trials · August 2026 BACKGROUND: Obesity is a growing epidemic associated with cardiovascular disease (CVD). The RESILIENCE study aimed to understand the factors underlying heterogeneity in CVD development among individuals with obesity as well as the variability in response t ... Full text Link to item CiteUnderstanding end-user contexts and identifying design preferences of an artificial intelligence-based clinical decision support tool for early autism detection.
Journal article JAMIA Open · August 2026 OBJECTIVES: Building on innovations for autism detection-where artificial intelligence (AI)-based models monitor clinical data within electronic health records-this study evaluates the context for clinical decision support (CDS) deployment and identifies d ... Full text Link to item CiteRecent Grants
1/3 CTSA UM1 at Duke University
ResearchFaculty Member · Awarded by National Institutes of Health · 2025 - 2032Duke Ophthalmology Mentored Physician Scientist Program
Inst. Training Prgm or CMEMentor · Awarded by National Institutes of Health · 2026 - 2031Computational Biology and Bioinformatics Training Grant
Inst. Training Prgm or CMEMentor · Awarded by National Institutes of Health · 2026 - 2031View All Grants
Education
University of California, Berkeley ·
2011
Ph.D.