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Jeffery Talbert

Department Chair

Jeffery Talbert

Department Chair

Professor

Academic Appointment(s)

Medical College of Georgia
Department of Artificial Intel & Health

School of Public Health
Department of Biostatistics, Data Science, & Epidemiology

Other Duties

GRA Eminent Scholar, AI and Health, Artificial Intelligence & Health

Bio

Jeffery Talbert, Ph.D., FAMIA, Professor and Department Chair in AI and Health and Georgia Research Alliance Eminent Scholar at the Medical College of Georgia, Augusta University.

  • JETALBERT@augusta.edu
  • (706) 721-2243
  • 1474 Laney Walker Blvd. Pavilion 3, Augusta, GA, 30912
  • Personal Website

Education

  • Ph.D., Political Science and Governme Texas A&M University, 1995

  • MA, Political Science and Governme Texas A&M University, 1991

  • BS, Political Science and Governme Texas A&M University, 1989

Certifications

  • Fellow, American Medical Informatics Association American Medical Informatics Association, 2020

Teaching Interests

Health informatics and outcomes analysis, health policy analysis, research design and methods, pharmaceutical outcomes and policy.

Scholarship

Selected Recent Publications

  • Machine learning approaches to predicting medication nonadherence: a scoping review., 2025
    Journal Article, Academic Journal
  • Cannabis use disorder risks among Medicaid enrollees with comorbid psychiatric illnesses: 2012–2021, 2025
    Journal Article, Academic Journal
  • Using Machine Learning to Assess Factors Associated with North American Pharmacist Licensure Examination Performance, 2025
    Journal Article, Academic Journal
  • Effects of the Communities That HEAL intervention on initiation, retention, and linkage to medications for opioid use disorder (MOUD): A cluster randomized wait-list controlled trial, 2025
    Journal Article, Academic Journal
  • HEALing Communities Study: Data measures for supporting a community-based intervention to reduce opioid overdose deaths., 2025
    Journal Article, Academic Journal

Research Interests

My research is focused on public health informatics, evidence-based policy, and health care outcomes. Current projects include the NIH funded Rapid Actionable Data for Opioid Response in Kentucky (RADOR-KY) that uses machine learning to predict future opioid overdoses at the community level.