Earn credit at your own pace through May 31, 2029 and continue to access your videos until June 1, 2036. See below for detailed information and learning outcomes.
This course offers 20 CME following completion of an online test.
Video content for this Online Course will be available to view until June 1, 2036, 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:
- Analyze the basics of artificial intelligence and its value in radiology.
- Create a practical framework for implementation of AI in clinical settings.
- Describe radiology applications of AI and summarize research and education approaches.
- Explain key perspectives of AI ethics, legal considerations, and human-centric AI.
Module 1: Getting to Know AI
- Overview of Radiology Artificial Intelligence: Latest Progress—Tessa Cook, MD, PhD
- Primer on Artificial Intelligence (AI): Deep Learning, Natural Language Processing and Large Language Models, Generative AI, Agentic AI, and Radiomics—Hyun Soo Ko, MD
- Artificial Intelligence Can Improve Radiology Workflow Efficiency By Automating Noninterpretive Tasks—Linda Moy, MD
- Artificial Intelligence to Improve Radiology Imaging Interpretation—Shandong Wu, PhD
Module 2: AI Clinical Implementation
- Legal and Ethical Considerations in AI Implementation—Julian Rivera, JD
- Artificial Intelligence Deployment—Tessa Cook, MD, PhD
- Artificial Intelligence (AI) Regulation and Governance: A Practice Perspective On How to Govern Assessment, Deployment, and Maintenance of AI Algorithms—Melissa Davis, MD, MBA
- Panel Discussion—Linda Moy, MD (Moderator); Julian Rivera, JD; Tessa Cook, MD, PhD; Melissa Davis, MD, MBA
Module 3: Going Beyond Images to Multimodality
- Medical Imaging Dataset Curation for Artificial Intelligence—Heather Whitney, PhD
- Multimodal Foundation Models in Radiology—Christian Bluethgen, MD
- Physics and Artificial Intelligence in CT—Lifeng Yu, PhD
- Panel Discussion—Heather Whitney, PhD; Christian Bluethgen, MD; Lifeng Yu, PhD
Module 4: AI Use Cases in Subspecialties: Breast, Neuro, Abdominal, and MSK
- Breast Imaging Artificial Intelligence—Constance Lehman, MD, PhD
- Artificial Intelligence in Neuroradiology—Paulo Kuriki, MD
- Artificial Intelligence in Abdominal Imaging—Yee Ng, MD
- Current and Emerging Applications of AI in Musculoskeletal Imaging—Ali Guermazi, MD
Module 5: AI Use Cases in Subspecialties: Peds, Cardiothoracic, IR, NM
- Pediatric Radiology Artificial Intelligence—Edward Lee, MD, MPH
- Artificial Intelligence in Cardiothoracic Imaging: From Decision Support to Prognostic Biomarkers—Fernando Kay, MD
- Applications of Artificial Intelligence in Interventional Radiology—Satvik Tripathi
- Nuclear Medicine AI—Babak Saboury, MD
Module 6: AI Research and Education
- Demonstration of an Artificial Intelligence Model Development Process (From A to Z) in Radiology—Dooman Arefan, PhD
- Artificial Intelligence Research in Radiology: Team, Approach, and Direction—Shandong Wu, PhD
- Clinically Fluent, AI Literate: Teaching Radiologists About and With AI—Justin Peacock, MD, PhD
- Panel Discussion—Shandong Wu, PhD (Moderator); Dooman Arefan, PhD; Justin Peacock, MD, PhD
Module 7: Humanity and AI
- Radiologist-Artificial Intelligence Collaboration and Teaming—Florence Doo, MD
- Bias and Fairness of Artificial Intelligence in Radiology: Current State and Future Directions—Judy Gichoya, MD, MS
- Radiologists Fit in AI-Powered Radiology Services That Are Radiologist-Centered—Eduardo Barbosa, MD, MBA
- Panel Discussion—Charles Kahn, Jr., MD, MS (Moderator); Florence Doo, MD; Judy Gichoya, MD, MS; Eduardo Barbosa, MD, MBA
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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 20 AMA PRA Category 1 Credits™. Physicians should claim only the credit commensurate with the extent of their participation in the activity.
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