ABAIM Advanced Course

The ABAIM AI in Medicine Advanced Course is a comprehensive, two-day course on advanced 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 designed for graduates of the ABAIM Introductory Course as well as attendees who are familiar with basic AI and data science concepts.

This course will provide a more in-depth look at concepts such as:

  • Bayes' Theorem
  • Federated Learning
  • Digital Twins
  • How to review a paper
  • And more

About the advanced course:

  • Similar to the Introductory 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
  • This course will prepare you for the Advanced Educational Certification

Schedule (All times ET)

Day 1
9:00 am - 10:15 am

Orientation to the ABAIM
Artificial Intelligence in Medicine Advanced Course

I. Introduction to Artificial Intelligence
- Faculty and attendee introductions

10:15 am - 10:30 am

Short Break

10:30 am - 11:30 am

I. Introduction to Artificial Intelligence
- Basic Concepts of Artificial Intelligence (Modules 1.1-1.5)

11:30 am - 12:30 pm

Lunch Session
Orange and Data Science

12:30 pm - 1:30 pm

I. Introduction to Artificial Intelligence (continued)
- History of Artificial Intelligence (Module 2.1)
- History of Artificial Intelligence in Medicine (Module 3.1)

II. Data Science and Artificial Intelligence in the Current Era
- Healthcare Data and Databases (Modules 4.1-4.4)

1:30 pm - 1:45 pm

Short Break

1:45 pm - 3:00 pm

II. Data Science and Artificial Intelligence in the Current Era (continued)
- Machine and Deep Learning (Part I)(Modules 5.1-5.12)

3:00 pm - 3:30 pm

Long Break

3:30 pm - 5:00 pm

II. Data Science and Artificial Intelligence in the Current Era (continued)
- Machine and Deep Learning (Project Design and Execution)

5:00 pm - 6:00 pm

Networking

Schedule (All times ET)

Day 2
10:00 am - 11:15 am

Review of Day 1

II. Data Science and Artificial Intelligence in the Current Era
- Machine and Deep Learning (Part II)(Modules 5.13-5.17)
- Assessment of Model Performance
- Issues with Machine and Deep Learning

11:15 am - 11:30 am

Short Break

11:30 am - 12:30 pm

II. Data Science and Artificial Intelligence in the Current Era (continued)
- Other Key Concepts in Artificial Intelligence (Modules 6.1-6.4)

12:30 pm - 1:30 pm

Lunch Session
How To Review a AI in Medicine Paper

1:30 pm - 2:30 pm

III. The Current Era of Artificial Intelligence in Medicine
- Clinician Cognition and AI in Medicine (Modules 7.1-7.6)
- Artificial Intelligence in Subspecialties (Modules 8.1-8.5)

IV. The Future of Artificial Intelligence and Application in Medicine
- Key Concepts of the Future of AI (Modules 10.1-10.2)
- The Future of Artificial Intelligence in Medicine (Module 11.1)

2:30 pm - 2:45 pm

Short Break


2:45 pm - 4:00 pm

AI in Medicine Demonstration and Final Q&A

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