Earn credit at your own pace through February 21, 2024 and continue to access your videos until February 20, 2031. See below for detailed information and learning outcomes.
This course offers 3.5 CME following completion of an online test.
Video content for this Online Course will be available to view until February 20, 2031, which is ten years following the issuance date of this course. ARRS reserves the right to remove video content before the end of the ten year period. Video content that contradicts current science or misleads the viewer based on changes to accepted clinical practice may be removed on a case-by-case basis.
Learning Outcomes and Modules
After completing this course, the learner should be able to:
- Discuss the basics of Machine Learning and Artificial Intelligence
- Explain how AI algorithms can be affected by bias
- Recognize the impact of AI systems on clinical reasoning
- Evaluate new AI claims and offerings and separate the hype from reality in Radiology AI
- Discuss how Radiology AI is being used currently in cardiothoracic imaging
- Reference future developments in AI in Radiology
- Recognize some ethical considerations in Radiology AI
- Radiology AI: Beyond the Hype—John Banja, MD
- The Basics of Machine Learning and AI—Steven Li, MA
- Bias in AI—Michael Bruno, MD
- AI in Lung Imaging and Cardiac Radiomics—Anthony Reeves, Ph.D
- AI and Clinical Reasoning: Mirror or Heuristics—David Chartash, Ph.D
- The Road Ahead for AI in Radiology—Charles Kahn, MD
ARRS is accredited by the Accreditation Council for Continuing Medical Education (ACCME) to provide continuing medical education activities for physicians.
The ARRS designates this enduring material for a maximum of 3.50 AMA PRA Category 1 Credits™. Physicians should claim only the credit commensurate with the extent of their participation in the activity.
View the ARRS Return Policy.