AI Fundamentals for Healthcare Professionals

This is a virtual course. 

AI Fundamentals for Healthcare Professionals is a comprehensive virtual educational program designed to equip clinicians, administrators, and healthcare staff with the knowledge and practical insight needed to understand and apply artificial intelligence responsibly in healthcare settings. Through an accessible, real‑world–focused curriculum, participants will build a strong foundation in AI concepts and healthcare data, explore clinical and operational use cases such as decision support, imaging, predictive analytics, and workflow optimization, and examine critical issues of ethics, bias, performance, and trust. 

Target audience

This activity is intended for physicians, nurses, quality & safety professionals, healthcare administrators & pharmacists.

Learning objectives

Upon completion of this activity, participants will be able to:

1. Develop a shared AI vocabulary and conceptual foundation
2. Describe the data that powers AI systems and identify their limitations
3. Relate core AI concepts to real‑world clinical and operational workflows
4. Describe the value of AI within and beyond direct clinical care
5. Critically assess AI tools for appropriateness, performance, and risk
6. Apply principles that ensure safe and equitable use of AI
7. Integrate appropriate trust in, and adoption of, AI-enabled tools
8. Identify rapidly emerging AI tools that clinicians are already using
9. Measure the impact and value of AI tools in healthcare settings
10. Integrate AI use with standards of clinical professionalism

Registration instructions

Cancellation Policy:
Registrations cancelled on or before May 22, 2026 will be refunded, less a $455 administrative fee. Registrations cancelled after May 22, 2026 will not be refunded.

Contact Maxine Harney if you require assistance in cancelling your online registration.

Please note:

Registration fee includes:

• All 13 weekly virtual, live sessions
• Reading materials & resources
• Access to session recordings
• 26.00 Continuing Education (CE) Credits

Additional information

Center for AI and Biomedical Informatics in a Learning Health System (CAIBILS) & Mass General Brigham

Faculty credentials

Course Co-Directors

David W. Bates, MD, MSc
Director, Center for Artificial Intelligence and Bioinformatics in the Learning Healthcare System (CAIBILS), Mass General Brigham
Professor of Medicine, Harvard Medical School

Hossein Estiri, PhD
Investigator, Massachusetts General Hospital
Associate Professor of Medicine, Harvard Medical School

Li Zhou, MD, PhD
Director, MTERMS Lab, Mass General Brigham
Lead Investigator, Brigham and Women’s Hospital
Professor of Medicine, Harvard Medical School

Faculty

Xinsong Du, PhD
Postdoctoral Research Fellow, Brigham and Women’s Hospital & Harvard Medical School

Jonathan Einbinder, MD, MPH
Vice President of Advanced Data Analytics and Coding, CRICO – Risk Management Foundation
Professor of Medicine, Harvard Medical School
Attending Physician, Brigham and Women’s Hospital

Nina Jain, MD, MBA, MSc
Senior Medical Director, Population Health, Mass General Brigham

Ramin Khorasani, MD
Radiology Quality Vice Chair and Assistant Chief Medical Officer, Mass General Brigham
Philip H. Cook Professor of Radiology, Harvard Medical School
Director, Center for Evidence Based Imaging, Brigham and Women’s Hospital

Joe Kvedar, MD
Professor of Dermatology, Harvard Medical School
Editor-in-Chief, npj Digital Medicine

Ronilda Lacson, MD
Research Scientist & Associate Director, Center for Evidence-Based Imaging, Brigham and Women’s Hospital
Associate Professor, Harvard Medical School

Anna C. F. Lewis, PhD
Member of the faculty, Department of General Internal Medicine, Mass General Brigham, Harvard Medical School
Affiliate faculty, Broad Institute of MIT and Harvard

Rebecca Mishuris, MD, MPH, MS
VP and Chief Health Information Officer, Mass General Brigham

Shawn Murphy, MD, PhD
Chief Research Information Officer, School of Medicine, University of Washington 
Director, Institute of Translational Health Sciences, University of Washington
Professor of Biomedical Informatics and Medical Education, Neurology, University of Washington

Kourosh Ravvaz, MD, PhD
Senior Data Scientist, Mass General Brigham Digital
Lecturer, Division of General Internal Medicine, Department of Medicine, Harvard Medical School

Jorgé A. Rodriguez, MD
Clinician-Investigator, Brigham and Women’s Hospital
Assistant Professor, Harvard Medical School
Assistant Chief Medical Informatics Officer of Ambulatory, Mass General Brigham

Lipika Samal, MD, MPH
Associate Professor of Medicine, Harvard Medical School

Liqin Wang, PhD
Assistant Professor, Brigham and Women’s Hospital & Harvard Medical School

Accreditation

In support of improving patient care, Mass General Brigham is jointly accredited by the Accreditation Council for Continuing Medical Education (ACCME), the Accreditation Council for Pharmacy Education (ACPE), and the American Nurses Credentialing Center (ANCC), to provide continuing education for the healthcare team.

Credit Designation Statements

AMA PRA Category 1 Credits^TM
Mass General Brigham designates this live activity for a maximum of 26.00 AMA PRA Category 1 Credits™. Physicians should claim only the credit commensurate with the extent of their participation in the activity.

Nursing
Mass General Brigham designates this activity for 26.00 ANCC contact hours. Nurses should only claim credit commensurate with the extent of their participation in the activity.

Pharmacy
This activity provides 26.00 contact hours (26.00 CEUs) of continuing education credit. ACPE Universal Activity Number (UAN): JA0007437-0000-26-008-L99-P