Catch up on the top radiology content of the past week.
Commentary|Videos|February 25, 2026
Assessing the Potential Impact of Agentic AI in Radiology: An Interview with Nina Kottler, MD
Author(s)Jeff Hall
In a recent interview, Nina Kottler, M.D., discussed the agility of agentic AI to achieve system-level goals in radiology, the need for transparency and how agentic AI may affect the future of radiology.
Advertisement
Advertisement
While convolutional neural networks, multimodal AI and large language models have dominated the discourse thus far with the evolution of AI in radiology, agentic AI represents more of an adaptive system-level approach to achieving goals, according to Nina Kottler, M.D., MS, FSIIM, FAIM.
Related to this article
In the second of a two-part podcast episode, Lauren Nicola, MD, Christoph Wald, MD, PhD, MBA, and Peter Shen discuss challenges with evaluating value and ROI for AI software, the physician time required to do so, and possible solutions to facilitate improved clarity and consistency with AI reimbursement.
Catch up on the top radiology content of the past week.
While AI tools abound in radiology, how many AI-enabled software products have incorporated insights from clinical radiologists?
Does fractional flow reserve (FFR) or quantitative plaque burden from CCTA provide greater prognostic insight into coronary disease?
In the first of a three-part podcast episode, Wendie Berg, MD, PhD, FACR, FSBI, Manisha Bahl, MD, and Amy Patel, MD share insights on the utility of AI in breast imaging with respect to potential advantages, current concerns and future directions.
Catch up on the most-well viewed radiology content in September 2026.
Catch up on the most well-viewed video interviews from Diagnostic Imaging in September 2026.
Advertisement
Advertisement