ABAIM Introductory Course

Date

Oct 07 - 08 2022

Time

EDT
9:00 am - 5:00 pm

The ABAIM AI in Medicine Introductory 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. This course is for all who are interested in having an overall review of concepts and applications in artificial intelligence in clinical medicine and healthcare.

About the course:

  • The format is “flipped” in that much of the review will be faculty discussing (not presenting) slides
  • In addition, the attendees are encouraged to ask questions throughout the sessions
  • There will also be a “pre” and “post” review course assessment with half the number of questions (50 questions) as the certification assessment (110 questions).

This course as well as independent study will prepare any attendee for the ABAIM AI in Medicine Assessment and Certification (110 questions in 2 hours).



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Hourly Schedule

Day 1

9:00 - 10:15
Orientation to the ABAIM Artificial Intelligence in Medicine review course</br> I. Introduction to Artificial Intelligence
-Faculty and attendee introductions
10:15 - 10:30
Short Break
10:30 - 11:30
I. Introduction to Artificial Intelligence (Continued)
- Basic Concepts of Artificial Intelligence (Modules 1.1-1.5)
11:30 - 12:30
LUNCH SESSION (Data Science Project Workflow and Tips)
12:30 - 1:30
I. Introduction to Artificial Intelligence (Continued)
- History of Artificial Intelligence (Module 2.1) - History of Artificial Intelligence in Medicine (Module 3.1)
Speakers:
Alfonso Limon, Anthony Chang
1:30 - 1:45
Short Break
1:45 - 3:00
II. Data Science and Artificial Intelligence in the Current Era
- Healthcare Data and Databases (Modules 4.1-4.4), - Machine and Deep Learning (Part I)(Modules 5.1-5.8)
3:00 - 3:30
Long Break
3:30 - 5:00
II. Data Science and Artificial Intelligence in the Current Era (continued)
- - Machine and Deep Learning (Part II)(Modules 5.9-5.12) and Deep Learning (Part II)(Modules 5.9-5.12)
5:00 - 6:00
Networking

Day 2

10:00 - 11:15
Review of Day 1, II. Data Science and Artificial Intelligence in the Current Era
- Machine and Deep Learning (Part III)(Modules 5.13-5.17) - Assessment of Model Performance - Issues with Machine and Deep Learning
11:15 - 11:30
Short Break
11:30 - 12:30
II. Data Science and Artificial Intelligence in the Current Era (continued)
12:30 - 1:30
Lunch Session (Ethics in AI in Healthcare)
1:30 - 2:30
II. Data Science and Artificial Intelligence in the Current Era (continued)
- Other Key Concepts in Artificial Intelligence (Modules 6.1-6.4)
2:30 - 2:45
Short Break
2:45 - 4:00
II. Data Science and Artificial Intelligence in the Current Era (continued), IV. The Future of Artificial Intelligence and Application in Medicine
- Clinician Cognition and AI in Medicine (Modules 7.1-7.6), - Artificial Intelligence in Subspecialties (Modules 8.1-8.5), Key Concepts of the Future of AI (Modules 10.1-10.2) - The Future of Artificial Intelligence in Medicine (Module 11.1), Final Q&A
Alfonso Limon
Alfonso Limon
Data Science Consultant
Highly effective technical director with proven accomplishments in a variety of engineering and medical applications combining mathematics, physics, and machine learning. Primarily focused on delivering state-of-the-art solutions impacting competitive business advantage– over a decade of experience building teams, designing complex data-driven projects, leading timeline-driven research programs, building milestone consensus for investors, and pitching technical goals to venture capitalists.
Anthony Chang
Anthony Chang
Chair, ABAIM
After his cardiology training at the Children’s Hospital of Philadelphia with his research interest in mathematics and chaos theory in biomedicine, Dr. Anthony Chang was an attending cardiologist in the cardiovascular intensive care unit of Boston Children’s Hospital and an assistant professor at Harvard Medical School. Throughout his career as a pediatric cardiac intensive care physician, he has been interested in applications of biomedical data to decision-making. He completed his Masters of Science (MS) in Data Science with a sub-specialization in artificial intelligence from Stanford School of Medicine. He is also a computer scientist-in-residence at Chapman University. He is currently the Chief Intelligence and Innovation Officer and Medical Director of the Heart Failure Program at Children’s Hospital of Orange County. He is the founder and medical director of the Medical Intelligence and Innovation Institute (MI3) that is supported by the Sharon Disney Lund Foundation. The institute, founded in 2015, is dedicated to the introduction and implementation of artificial intelligence in medicine and was the first institute of its kind in a hospital. He intends to build a clinician-computer scientist interface with a nascent society (the Medical Intelligence Society) and is the editor-in-chief of Intelligence-based Medicine, the accompanying journal for his book, Intelligence-Based Medicine: Artificial Intelligence and Human Cognition in Clinical Medicine and Healthcare. He is the organizing chair for Artificial Intelligence in Medicine (AIMed) meetings around the world, the largest and most comprehensive clinician-led meetings that focus on applications of artificial intelligence in medicine and the dean of the nascent American Board of Artificial Intelligence in Medicine (ABAIM).

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