ARRS Clinical Artificial Intelligence in Radiology 2026 – Videos + eBook

Artificial intelligence is rapidly transforming medical imaging, from image interpretation and workflow automation to clinical decision support, research, education, and patient care.

ARRS Clinical Artificial Intelligence in Radiology 2026 provides a comprehensive and practical exploration of artificial intelligence in radiology, helping radiologists and imaging professionals understand both the technology behind modern AI systems and the challenges involved in integrating them into clinical practice.

The program progresses from the fundamentals of artificial intelligence to real-world implementation and advanced applications. Topics include deep learning, natural language processing (NLP), large language models (LLMs), generative AI, agentic AI, radiomics, multimodal foundation models, AI governance, regulation, ethics, bias and fairness.

The course also examines how AI is currently being applied across major radiology subspecialties, including breast, neuro, abdominal, MSK, pediatric, cardiothoracic, interventional radiology, and nuclear medicine.

A major focus is placed on the evolving relationship between the radiologist and artificial intelligence, including how AI can support radiologists while maintaining human-centered, radiologist-led healthcare services.

Course Content

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 & 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 – Pediatrics, Cardiothoracic, IR & Nuclear Medicine

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

Demo Video :

Learning Outcomes

After completing the course, learners should be able to:

• Analyze the fundamentals of artificial intelligence and its value in radiology.
• Develop a practical framework for implementing AI within clinical settings.
• Describe current and emerging applications of artificial intelligence across radiology.
• Understand the role of deep learning, NLP, LLMs, generative AI and agentic AI in medical imaging.
• Discuss approaches to AI research and radiology education.
• Explain important ethical, legal, regulatory and governance considerations surrounding clinical AI.
• Understand bias, fairness and human-centered AI.
• Evaluate how radiologists can effectively collaborate with AI-powered systems.

Major Topics Covered

Artificial Intelligence in Radiology • Radiology AI • Deep Learning • Large Language Models (LLMs) • Generative AI • Agentic AI • Natural Language Processing • Radiomics • AI Workflow Automation • AI Image Interpretation • Clinical AI Implementation • AI Governance • AI Regulation • AI Ethics • Multimodal Foundation Models • Medical Imaging Datasets • AI in CT • Breast Imaging AI • Neuroradiology AI • Abdominal Imaging AI • Musculoskeletal AI • Pediatric Radiology AI • Cardiothoracic Imaging AI • Interventional Radiology AI • Nuclear Medicine AI • AI Research • AI Education • AI Bias and Fairness • Radiologist-AI Collaboration

Target Audience

This educational program is particularly relevant for:

• Radiologists
• Radiology residents and fellows
• Medical imaging professionals
• Radiology researchers
• Academic radiologists
• Nuclear medicine physicians
• Interventional radiologists
• Medical physicists
• Healthcare professionals interested in artificial intelligence and medical imaging

Product Details

Course: ARRS Clinical Artificial Intelligence in Radiology
Release Year: 2026
Provider: ARRS
Category: Radiology / Artificial Intelligence / Medical Imaging
Content Included: Video Lectures + eBook
Language: English