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ForwardJune 19, 2026 Common AI Use Cases in Clinical Practice
Goal: Connect AI concepts to real-world workflows
- Clinical decision support (risk prediction, alerts)
- Imaging and pathology AI
- Predictive analytics (readmissions, deterioration)
- NLP for clinical documentation and chart review
- Generative AI for clinical notes, patient messages, summarization
- Remote monitoring and digital biomarkers
Activity: Case-based walkthroughs of real deployments
Target Audience
This activity is intended for physicians, nurses, quality & safety professionals, healthcare administrators & pharmacists.
Additional Information
Course Co-Directors
David W. Bates, MD, MSc
Chief Innovation Officer, Brigham & Women's Hospital
Professor, Harvard Medical School
Li Zhou, MD, PhD
Lead Investigator, Brigham & Women's Hospital
Professor of Medicine, Harvard Medical School
Hossein Estiri, PhD
Investigator, Mass General Research Institute
Associate Professor of Medicine, Harvard Medical School
Speakers
Rebecca Mishuris, MD
Ramin Khorasani, MD
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 CreditsTM
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): JAXXXXXX-XXXX-XX-XXX-XXX-X.