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American Board of Artificial Intelligence in Medicine Review Course (Virtual) April

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Want to learn about AI but don’t know where to start?

The American Board of Artificial Intelligence in Medicine Review Course is a comprehensive, two-day course on basic concepts in artificial intelligence in clinical medicine and healthcare designed by a team of clinician-data scientists as well as clinicians with an AI focus and data scientists who are involved in healthcare for all who are interested in having an overall review of concepts and applications in artificial intelligence in clinical medicine and healthcare. This course as well as the independent study will prepare anyone for the American Board of Artificial Intelligence in Medicine Assessment and Certification (100 questions in 3 hours).

Date: Apr. 23 – 24, 2021

Time: 9:00 am EDT – 6:00 pm EDT

Who Should Take This Course:
Clinicians, Healthcare Workers, Executives, Data Scientists, Trainees, Residents, Fellows, Entrepreneurs, Students, High School, Professional School, and University/College

Accredited Physician CME – Technologists Category A CE Credits

Agenda

Program Learning Objectives:

  1. Review the evolution of artificial intelligence in society as well as in medicine and healthcare.
  2. Understand the relevance of artificial intelligence in clinical medicine.
  3. Know the relevant aspects of data, information, and data bases in healthcare.
  4. Appreciate how clinicians think and how artificial intelligence can transform quality of decisions.
  5. Comprehend basic concepts in machine and deep learning and their applications.
  6. Follow the machine learning workflow and barriers to adoption in an organization.
  7. Assess the utility and application of natural language processing and cognitive computing.
  8. Evaluate the future aspects of artificial intelligence in clinical medicine and healthcare.
  9. Recognize important issues of ethics and bias of artificial intelligence in clinical medicine.
  10. Devise artificial intelligence strategies for healthcare organizations and companies.
  11. Explore intellectual and cultural similarities and differences between clinicians and data scientists.
  12. Understand the fundamentals of digital health entrepreneurship.