AI in Clinical Medicine
- Continuing Education
Deadline Approaching Enroll now to secure your seat.
Gain practical skills and insights to apply cutting-edge AI technologies in clinical medicine through expert-led sessions, real-world case studies, and interactive discussions in this live online course.
- Live Online
This is a three-day online course taught in real time.
Day 1-2: June 11, 12
Day 3: June 15
Clinicians who are already familiar with AI concepts, or who have previously completed the AI in Clinical Medicine course, may wish to enroll in only the final day.
$2,500
Please note: The registration fee for all three days is $2,500.
Attendees have the option to register for the first two days only ($1,900) or the last day only ($1,200).
Continuing Education
Three Days
The first two days (June 11-12) will cover the fundamental principles of AI.
The last day (June 15) will concentrate on practical strategies for integrating AI into clinical organizations and practices.
On This Page
Overview
Over the last few decades, the digitization of medical records has created opportunities for automation and data-driven clinical support for a wide range of routine clinical applications. Today, artificial intelligence (AI) is accelerating innovation in health care. We are on the cusp of revolutionizing how we care for patients in profound ways.
New technologies are available now to help you impact your practice. AI medical scribes, new research tools and diagnostic tests, and personalized treatment options are just a few applications of AI that are beginning to have a direct impact on clinicians and the patients they serve.
Up until now, most health care providers have not received formal training in artificial intelligence. Now is the time for physicians, nurses, advanced practice providers, and all allied health professionals to prepare for how AI is changing medical care.
This live online course focuses on cutting edge and exciting new applications of AI, including foundational principles and lessons learned that you will be able to take directly back to your practice. Over three days, you will hear from medical society leaders, academic leaders, and innovators from academia and industry.
Sessions will dive into the applications of AI in diagnosing diseases, predicting patient outcomes, patient monitoring, and personalizing treatment plans. Through lectures, field-specific break-out sessions, and real-world case studies, you will acquire the knowledge to harness AI’s potential to advance patient care, research, and health systems innovation. Faculty experts will explore the ethical implications, challenges, and opportunities inherent in integrating AI into modern health care practice.
During this course we will cut through the hype around AI to provide realistic, firsthand viewpoints into the potential of AI in clinical practice. Health care professionals, including physicians, nurses, nurse practitioners, physician assistants, and other practitioners are highly encouraged to join us for this transformational learning experience.
Learning Objectives
- Define the unique challenges and opportunities for integrating AI in specialized health care fields.
- Discuss the ethical considerations and potential biases in AI algorithms, especially in decision-making processes related to patient care, diagnosis, and treatment planning.
- Review the current status area of AI regulation and how it can impact health care.
- Assess the long-term quality and accuracy of AI technologies and their impact on patient care.
- Develop methods for integrating AI into medical education, including content generation, evaluation, and ensuring alignment with educational objectives.
Who Should Participate
Clinicians treating patients in any type of setting including, physicians, nurses, nurse practitioners, and clinical leaders
Schedule
All agenda sessions are in Eastern Time.
Thursday, June 11, 2026
Welcome
9:00-9:05 am
Keynote: Paging Dr. A.I.: How AI is Changing the Face of Clinical Care
9:05-9:50 am
Q&A
9:50-10:00 am
Learning the AI Lingo: Machine Learning, Deep Learning, and Large Language Models
10:00-10:45 am
A Look Into the Black Box: Technical Background for Clinicians
10:45-11:15 am
Medical Data as the Backbone of AI
11:15-11:45 am
Panel Discussion
11:45 am-12:15 pm
Break
12:15-12:45 pm
Chatbots in Health Care: A Historical Expedition
12:45-1:30 pm
AI Learning Revolution: Transforming Medical Education
1:30-2:15 pm
Ambient Scribes
2:15-2:45 pm
Panel Discussion and Q&A
2:45-3:15 pm
Break
3:15-3:30 pm
An AI designed drug for IPF: from preclinical development to phase II in under 3 years
3:30-4:00 pm
Precision Medicine: AI and Personalized Treatment in Oncology
4:00-4:30 pm
AI Powered Drug Repositioning and Clinical Trial Design
4:30-5:00 pm
Panel Discussion and Q&A
5:00-5:30 pm
Friday, June 12, 2026
Welcome
9:00-9:05 am
Keynote: Ethics and AI in Healthcare
9:05-9:50 am
AI for Pioneering Leadership in the Digital Era
9:50-10:35 am
Law and Regulation in AI
10:35-11:20 am
Panel Discussion and Q&A
11:20-11:50 am
Break
11:50 am-12:30 pm
Telemetry/Mhealth for early detection of heart failure exacerabation
12:30-1:05 pm
Brain computer interfaces and decoding speech
1:05-1:40 pm
Can Chat bots improve mental health?
1:40-2:15 pm
Panel Discussion and Q&A
2:15-2:45 pm
Break
2:45-3:00 pm
Bias in Risk Stratification for allocation and policy
3:00-3:35 pm
Robust, Fair and private AI
3:35-4:10 pm
Algorithmic bias in clinical scores and implications for AI
4:10-4:45 pm
Panel Discussion and Q&A
4:45-5:15 pm
Monday, June 15, 2026
Welcome
9:00-9:05 am
But I Want it Now!: Barriers to Clinical AI Implementation
9:05-9:35 am
How Can I Help You? Clinical Decision Support in the EHR
9:35-10:05 am
Implementing AI in your small practice
10:05-10:35 am
Hidden risks of AI in your practice
10:35-11:05 am
Panel Discussion and Q & A
11:05-11:35 am
Break
11:35-11:50 am
Money Talks: How AI Can Help You Improve Your Bottom Line
11:50 am-12:20 pm
AI and Reducing Healthcare Provider Burnout
12:20-12:50 pm
Why AI may be good for our health but hurt our wallets
12:50-1:20 pm
Panel Discussion and Q&A
1:20-1:50 pm
Break
1:50-2:20 pm
Study Hall -Clinical Applications: Pathology
2:20-3:20 pm
Study Hall -Clinical Applications: Endocrinology
2:20-3:20 pm
Study Hall -Clinical Applications: Dermatology
2:20-3:20 pm
Study Hall -Clinical Applications: Opthalmology
2:20-3:20 pm
Study Hall -Clinical Applications: Nursing
2:20-3:20 pm
Break
3:20-3:25 pm
Study Hall -Clinical Applications: Gastroenterology
3:25-4:25 pm
Study Hall -Clinical Applications: Critical Care
3:25-4:25 pm
Study Hall - Clincal Applications: Cardiology
3:25-4:25 pm
Study Hall - Clinical Applications: Radiology
3:25-4:25 pm
Study Hall - Clinical Applications: Surgery or Anesthesia
3:25-4:25 pm
Break
4:25-4:40 pm
Study Hall - Virtual demonstrations: Ambient Scribe from Abridge
4:40-5:40 pm
Study Hall - Virtual demonstrations: Leveraging clinician's expertise with Agentic AI
4:40-5:40 pm
Study Hall - Virtual demonstrations: Evidence search using OpenEvidence
4:40-5:40 pm
Study Hall - Virtual demonstrations: Doctronic
4:40-5:40 pm
Study Hall - Virtual demonstrations: Uptodate Expert AI
4:40-5:40 pm
Study Hall - Virtual demonstrations: Glasshealth's clinical decision support platform
4:40-5:40 pm
Faculty
Harvard Medical School Continuing Education attracts the best and brightest faculty from all around the world. As a student in this course, you’ll have access to outstanding course directors and faculty.
Course Directors
Maha Farhat, MD, MSc
Course Director
- Gil Omenn Associate Professor of Biomedical Informatics, Harvard Medical School
- Associate Physician, Pulmonary and Critical Care, Massachusetts General Hospital
- Affiliate in Global Health and Social Medicine, Harvard Medical School
Samir Kendale, MD, FASA
Course Director
- Assistant Professor of Anaesthesia, Harvard Medical School
- Medical Director of Anesthesia Informatics, Beth Israel Lahey Health
Isaac Kohane, MD, PhD
Course Director
- Chair of the Department of Biomedical Informatics, Harvard Medical School
- Marion V. Nelson Professor of Biomedical Informatics, Harvard Medical School
- Associate Professor of Medicine, Brigham and Women’s Hospital
Monica Agrawal, PhD
Assistant Professor, Duke University
Co-founder, Layer Health
Tyler Berzin, MD
Associate Professor of Medicine, Harvard Medical School
Rebecca Weintraub Brendel, JD, MD
Director, Harvard Medical School Center for Bioethics
Director, Master of Science in Bioethics Degree Program, Harvard Medical School
Associate Professor of Psychiatry, Harvard Medical School
Leo Celi, MD
Principal Research Scientist, Massachusetts Institute of Technology
Associate Professor, Harvard Medical School
Instructor, Harvard T.H. Chan School of Public Health
Associate Program Director Department of Medicine, Beth Israel Deaconess
Roxana Daneshjou, MD, PhD
Assistant Professor, Department of Biomedical Data Science and of Dermatology, Stanford University
Constance Leman, MD, PhD
Diagnostic Radiologist, Massachusetts General Hospital
Genevieve Melton-Meaux, MD, PhD
Professor, Division of Colon & Rectal Surgery, Department of Surgery, University of Minnesota
Director, Center for Learning Health System Sciences
Professor and Core Faculty Member, Institute of Health Informatics
Senior Associate Dean for Health Informatics and Data Science
Chief Health Informatics and AI Officer, Fairview Health Services
David Ouyang, MD
Assistant Professor of Cardiology; Assistant Professor of Medicine, Cedars Sinai
Pranav Rajpurkar, PhD
Assistant Professor of Biomedical Informatics, Harvard Medical School
Adam Rodman, MD
Instructor in Medicine, Beth Israel Deaconess Medical Center
Jean-Claude Saghbini, PhD
President & Chief Technology Officer, Lumeris Value-Based Care Enablement
Stanley Shaw, MD, PhD
Associate Dean for Executive Education, Harvard Medical School
Kun Yu, MD, PhD
Assistant Professor of Biomedical Informatics, Harvard Medical School
Nazlee Zebardast, MD MSc
Director of Glaucoma Imaging, Massachusetts Eye and Ear
Assistant Professor of Ophthalmology, Harvard Medical School
About the Program
AI Learning Opportunities
Harvard Medical School offers a range of AI-focused learning opportunities designed for health care leaders, clinicians, educators, and professionals, with flexible formats and durations to fit diverse needs.
| Learning Opportunity | Format | Duration | Audience |
|---|---|---|---|
| Leading AI Innovation in Health Care | Blended | 9 weeks | Health care administrators and industry leaders |
| Technology-Enabled Care Delivery: From Digital Medicine to AI | Blended | 2 months | Clinical, operational, and administrative leaders |
| AI in Clinical Medicine | Live Virtual | 3 days | Physicians and other clinicians |
| AI in Medicine: HMX Short Courses | Self-paced online | 3-4 hours each | Science and business professionals, clinicians |
| AI in Health Care: Strategies and Implementation | Self-paced and live virtual | 2 months | Business leaders and professionals |
| Technology and AI: Transforming Health Professions Education | Live Virtual | 2 months | Health care educators |
| AI-Driven Health Care Transformation | Self-paced and live virtual | 18 weeks | C-suite & senior innovation leaders |
Not sure which program is right for you? Talk to our AI in Health Care Program Advisor.
Request Information
Interested in learning more about this program? Sign up for details.
Course Fees
Registration Details
Tuition for AI In Clinical Medicine is listed below. You may register through our secure online environment and will receive an email confirmation upon receipt of your payment.
Prices include CME credit, electronic syllabus and access to recordings for 60 days after the course.
At the end of the registration process, a $10 non-refundable processing fee will be added to your registration.
| Role | Course Fee |
|---|---|
| Physician (MD/DO) | $2,500 |
| Nurse (RN/APRN) | $2,500 |
| PA | $2,500 |
| Psychologist | $2,500 |
| Resident/Fellow | $2,500 |
| Social Worker | $2,500 |
| Allied Health Professional / Other | $2,500 |
Please Note: The above price is for the full course fee (June 11-12, 15).
Additional Course Registration Options:
The first two days (June 11, 12) include Foundations and Pioneering Innovation sessions, designed for clinicians who are new to the fundamental principles of AI and how AI models work, or who would like a refresher before the final day of the course. The final day (June 15) will include Implementation and Applications sessions, focusing on more advanced topics in AI implementation and clinical application.
Clinicians who are already familiar with AI concepts, or who have previously completed the AI in Clinical Medicine course, may wish to enroll only in the final day, which will concentrate on practical strategies for integrating AI into clinical organizations and practices.
| Two Day Option (June 11, 12) | One Day Option (June 15) | |
|---|---|---|
| Course Fee | $1,900 | $1,200 |
| Early Registration Fee | $1,700 | $1,000 |
Accreditation
The Harvard Medical School designates this live activity for a maximum of 33.50 AMA PRA Category 1 Credit(s)™. Physicians should claim only the credit commensurate with the extent of their participation in the activity.
Harvard Medical School designates this Live Activity for a maximum of 33.50 ANCC contact hours.
Harvard Medical School has been authorized by the American Academy of PAs (AAPA) to award AAPA Category 1 CME credit for activities planned in accordance with AAPA CME Criteria. This activity is designated for 30.00 AAPA Category 1 CME credits. PAs should only claim credit commensurate with the extent of their participation.
Successful completion of this CME activity, which includes participation in the evaluation component, enables the participant to earn up to 33.50 MOC points in the American Board of Internal Medicine’s (ABIM) Maintenance of Certification (MOC) program. It is the CME activity provider’s responsibility to submit participant completion information to ACCME for the purpose of granting ABIM MOC credit.
This activity meets the criteria of the Massachusetts Board of Registration in Medicine for 1.50 credits of Risk Management Study
The American Medical Association (AMA) has an agreement of mutual recognition of continuing medical education (CME) credit with the European Union of Medical Specialists (UEMS). Additional information regarding this agreement may be found on the Union of European Medical Specialists website.
The Royal College of Physicians and Surgeons of Canada recognizes conferences and workshops held outside of Canada that are developed by a university, academy, hospital, specialty society or college as accredited group learning activities.