Enhancing Health Research with Machine Learning: Practical Case Studies Using the All of Us Researcher Workbench

Enhancing Health Research with Machine Learning: Practical Case Studies Using the All of Us Researcher Workbench

Machine learning is revolutionizing health research by enabling scalable analysis across complex datasets. The All of Us Research Program offers unprecedented access to a wealth of health data. To harness this potential, researchers must navigate the All of Us database structure, develop machine lea...

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Bibliographic Details
Main Authors: Jonathan R. Holt, Stefanee Tillman, Javan Carter, Edward Preble, Sheryl C. Cates, Daniel Brannock, Michael Long, John McCarthy, Leslie Zapata Leiva, Jamboor K. Vishwanatha, Toufeeq Syed, Legand Burge, Robert T. Mallet, Shelly Kowalczyk, Jennifer D. Uhrig, Megan A. Lewis
Format: Article
Language:English
Published: Taylor & Francis Group 2025-12-01
Series:Data Science in Science
Subjects:
All of Us Researcher Workbench
machine learning
artificial intelligence
electronic health records
training program
professional development
Online Access:https://www.tandfonline.com/doi/10.1080/26941899.2025.2523871
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