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.
Who Should Attend
This course was designed specifically for clinicians treating patients in any type of setting including:
- Physicians
- Nurses
- Nurse Practitioners
- Clinical leaders – Administrators
Learning Objectives
Upon completion of this activity, participants will be able to:
- 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.
