ABAIM Introductory Course

Date

Mar 04 - 05 2022

Time

EST
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).



Hourly Schedule

Day 1

9:00 - 10:15
Orientation to the ABAIM Artificial Intelligence in Medicine review course
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 (Entrepreneurship in AI in Medicine and Q&A)
12:30 - 1:30
II. Data Science and Artificial Intelligence in the Current Era
- History of Artificial Intelligence (Module 2.1)
- History of Artificial Intelligence in Medicine (Module 3.1)
- Healthcare Data and Databases (Modules 4.1-4.4)
1:30 - 1:45
Short Break
1:45 - 3:00
II. Data Science and Artificial Intelligence in the Current Era (continued)
- 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)
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 5.15-5.17)
- Assessment of Model Performance
- Evaluation of Classification Models
- Issues with Machine and Deep Learning
11:15 - 11:30
Short Break
11:30 - 12:30
- Machine and Deep Learning (Part III)(Modules 5.15-5.17)
- Assessment of Model Performance
- Evaluation of Classification Models
- Issues with Machine and Deep Learning
- Other Key Concepts in Artificial Intelligence (Modules 6.1-6.4)
12:30 - 1:30
Lunch Session (Ethics in AI in Healthcare)
12:30 - 1:30
III. The Current Era of Artificial Intelligence in Medicine
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)
1:30 - 1:45
Short Break
1:45 - 3:00
Post-Course Assessment or Miscellaneous Topics
Speakers:
Orest Boyko
Orest Boyko
Orest Boyko
Co-Chair, ABAIM
Orest B. Boyko MD PhD is an American Board of Radiology board certified radiologist with an additional ABR certificate of added qualifications in Neuroradiology. Dr Boyko has been an Associate Professor since 2007 at the University of Southern California in Los Angeles, California, and currently is part of the USC Bridge Institute housed in the USC Michelson Center for Convergent Bioscience on the main campus of USC. As a radiologist, Dr Boyko as been working in the AI research community as a physician consultant since December 2013 in multi-modal mining in healthcare in the research lab of Dr Tanveer Sayeda-Mahmood in the IBM Almaden Research Center 650 Harry Road, San Jose, CA 95120 which has developed natural language processing applications to the electronic health record to assist in clinical decision support. Dr Boyko has also been since its inception involved the currently concluding IBM Healthcare Initiative in Radiology called the IBM Medical Sieve Radiology Grand Challenge in initial cutting edge research development of a radiology and cardiology cognitive assistant. Recently, Dr Boyko accepted an invitation to chair the newly created Guerbet Digital Solutions AI Advisory Board and Guerbet initiate to create an AI community in conjunction with Applied Radiology. Dr Boyko is active in advancing learning initiatives for the field of AI and machine learning. Dr Boyko has co-authored over 100 papers and book chapters in the field of radiology, neuroradiology and MRI.