Focusing on the fundamentals of machine learning (ML) and artificial intelligence (AI) in radiology, as well as current clinical applications and future applied developments, participants in this Online Course will be better equipped to critically evaluate and implement ML and AI systems in their own imaging practices
Learning Outcomes and Lectures
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
Module 1
- Radiology AI: Beyond the Hype—John Banja, MD
- The Basics of Machine Learning and AI—Steven Li, MA
Module 2
- Bias in AI—Michael Bruno, MD
- AI in Lung Imaging and Cardiac Radiomics—Anthony Reeves, Ph.D
Module 3
- AI and Clinical Reasoning: Mirror or Heuristics—David Chartash, Ph.D
- The Road Ahead for AI in Radiology—Charles Kahn, MD
Date of issuance: February 22, 2021
Date of expiration: February 21, 2024
