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Advancing Family Medicine through Artificial Intelligence & Machine Learning

2022 AI / ML Grant Winners Header

Background

In Winter 2022, the American Board of Family Medicine Foundation (ABFM Foundation) launched its first Request for Proposal (RFP) process to solicit proposals from Family Medicine Departments and Divisions for grants to support the hiring of an Artificial Intelligence/Machine Learning (AI/ML) researcher embedded in the department. This RFP was designed to increase the capacity of AI/ML methods in Family Medicine for studying primary care research questions using real-world primary care data. Grants of up to $500,000 were provided. Funding from the ABFM Foundation will last four years from Fall 2022-Fall 2026 and then will require institutional commitment for the fifth year.

Intended Outcomes of AI/ML Faculty Support Grant

  • A sustained AI/ML researcher imbedded in a department
  • Two proposals for externally funded research (per department)
  • Three peer-reviewed publications (per department)
2022 AI / ML Grant Winners Header

Background

In Winter 2022, the American Board of Family Medicine Foundation (ABFM Foundation) launched its first Request for Proposal (RFP) process to solicit proposals from Family Medicine Departments and Divisions for grants to support the hiring of an Artificial Intelligence/Machine Learning (AI/ML) researcher embedded in the department. This RFP was designed to increase the capacity of AI/ML methods in Family Medicine for studying primary care research questions using real-world primary care data. Grants of up to $500,000 were provided. Funding from the ABFM Foundation will last four years from Fall 2022-Fall 2026 and then will require institutional commitment for the fifth year.

Intended Outcomes of AI/ML Faculty Support Grant

  • A sustained AI/ML researcher imbedded in a department
  • Two proposals for externally funded research (per department)
  • Three peer-reviewed publications (per department)

2022 Grant Recipients

Following a rigorous review and scoring process by an external AI/ML expert review panel, the following institutions were awarded funding.

Winston Liaw, MD, MPH

University of Houston

Principle Investigator: Winston Liaw, MD, MPH

Project Title

Primary Care Forecast: Using Social Risk Factors and Actionable, Explainable Artificial Intelligence/Machine Learning to Prevent the Progression of Diabetes Complications

Co-Investigators

Ioannis A. Kakadiaris, PhD; LeChauncy Woodard, MD, MPH; Omolola Adepoju, PhD, MPH

John S. Maier, PhD, MD

University of Pittsburgh

Principle Investigator: John S. Maier, MD, PhD

Project Title

Growing Primary Care Informatics using AI/ML to Understand Patients Not Just Diseases

Co-Investigators

Tracey Conti, MD; Shyam Visweswaran, MD, PhD; José Abad, MD

Gene Kallenberg, MD

University of California, San Diego

Principle Investigator: Gene Kallenberg, MD

Project Title

Building AI/ML Capacity in the UCSD Department of Family Medicine

Co-Investigators

Ming Tai-Seale, PhD, MPH; Lucila Ohno-Machado, MD, PhD, MBA; Christopher Longhurst, MD

AI/ML Fellow:

Ammar Mandvi, MD

Carlos Roberto Jaén, MD, PhD

University of Texas, San Antonio

Principle Investigator: Carlos Roberto Jaén, MD, PhD

Project Title

Harnessing Complexity: Applying AI/ML to discover solutions of multi-morbidity in Primary Care

Co-Investigators

Meredith Nahm Zozus, PhD; Zhu Wang, PhD; Robert L. Ferrer, MD, MPH; David A. Katerndahl, MD, MA

AI/ML Fellows:

Shorabuddin Syed, PhD; Yun Shi, MD, PhD

find out more about our work and research in primary care AI/ML