Dr. Paul Chang shares his insights on the role of foundation models and agentic AI in radiology at RSNA 2025.
Key Details
- 1Dr. Paul Chang, from the University of Chicago, is featured in an RSNA 2025 interview.
- 2He discusses the current maturity of AI in radiology, referencing the 'Four Horsemen of AI immaturity.'
- 3Highlights include the potential and value of foundation models in improving radiology workflows.
- 4The concept of 'agentic AI' is explored as an emerging trend in imaging AI.
Why It Matters

Source
AuntMinnie
Related News

Toronto Study: LLMs Must Cite Sources for Radiology Decision Support
University of Toronto researchers found that large language models (LLMs) such as DeepSeek V3 and GPT-4o offer promising support for radiology decision-making in pancreatic cancer when their recommendations cite guideline sources.

AI Tool Outperforms Radiologists in Pancreatic Cancer Detection
AI demonstrated superior accuracy over radiologists in detecting pancreatic cancer, according to new comparative data.

AI Model Shows Promise for Detecting Meningiomas on Skull X-rays
South Korean researchers developed an AI model that detects meningiomas on skull x-rays, showing high accuracy in initial tests.