AI in Clinical Medicine
- Continuing Education
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 course.
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Overview
Over the last two decades, the digitization of medical records created opportunities for automation and data-driven clinical support for a range of routine clinical applications. Today, artificial intelligence (AI) is accelerating innovation in clinical medicine. 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 medical practitioners have not received formal training in artificial intelligence. Recognizing that now is the time for physicians and allied health care professionals to prepare for how AI is changing medical care, Harvard Medical School is offering this new continuing education course, AI in Clinical Medicine.
This live virtual 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 two days, you will hear from medical society leaders, academic leaders, and innovators from academia and industry.
Sessions will delve into the applications of AI in diagnosing diseases, predicting patient outcomes, 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 improve patient care and medical research. Faculty experts will explore the ethical implications, challenges, and opportunities inherent in integrating AI into medical 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. Physicians and medical practitioners of all kinds are highly encouraged to join us for this transformational learning experience.
This course will be delivered in English with live AI (artificial intelligence)-based interpretation in Spanish and Portuguese offered as a supplemental feature. All course materials will be in English.
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.
Participant Types
Clinicians treating patients in any type of setting including, physicians, nurses, nurse practitioners, and clinical leaders
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.
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
Eli van Allen, MD
Associate Professor of Medicine, Harvard Medical School
Chief, Division of Population Sciences, Dana Farber Institute
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
I. Glenn Cohen, JD
James A. Attwood and Leslie Williams Professor of Law
Deputy Dean
Faculty Director, Petrie-Flom Center for Health Law Policy, Biotechnology & Bioethics, Harvard Law School
Catherine Choi, MD
Abridge
Roxana Daneshjou, MD, PhD
Assistant Professor, Department of Biomedical Data Science and of Dermatology, Stanford University
Vikram Khurana, MD, PhD
Associate Professor of Neurology at Harvard Medical School
Chief of the Division of Movement Disorders at Brigham and Women’s Hospital
Constance Leman, MD, PhD
Diagnostic Radiologist, Massachusetts General Hospital
Zachary Lipton, PhD
Associate Professor of Machine Learning, Carnegie Mellon
Arjun Manrai, PhD
Assistant Professor, Department of Biomedical Informatics, Harvard Medical School
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
Jane Moran
Chief Information and Digital Officer, Mass General Brigham
Ziad Obermeyer, MD
University of California, Berkeley School of Public Health
David Ouyang, MD
Assistant Professor of Cardiology; Assistant Professor of Medicine, Cedars Sinai
Natalie Pageler, MD
Clinical Professor, Peds/Clinical Informatics
Clinical Professor, Medicine - Biomedical Informatics Research
Chief Medical Information Officer, Stanford Children's Health
Program Director, Clinical Informatics Fellowship, Stanford University
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
Collin M. Stultz, MD, PhD
Nina T. and Robert H. Rubin Professor, Electrical Engineering & Computer Science and Institute for Medical Engineering & Science, Massachusetts Institute of Technology
Director, Harvard-MIT Health Sciences & Technology, Massachusetts Institute of Technology
Associate Director, Institute for Medical Engineering and Science, Massachusetts Institute of Technology
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
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Course Fees
Fee Disclaimer
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 | Standard Price |
|---|---|
| Physician (MD/DO) | $1,900.00 |
| Nurse (RN/APRN) | $1,900.00 |
| Resident/Fellow | $1,900.00 |
| Allied Health Professional / Other | $1,900.00 |
Accreditation
The Harvard Medical School designates this live activity for a maximum of 22.50 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 22.50 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 22.50 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 22.50 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 2.00 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 Specialties (UEMS). Additional information regarding this agreement may be found on the European Union of Medical Specialties 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.