Jason Poff explains 5-step process to evaluate radiology AI

Radiology artificial intelligence (AI) continues to gain traction in medical imaging, promising enhanced detection and improved workflow efficiency. However, selecting the right AI tool requires careful evaluation. Jason Poff, MD, a radiologist at Greensboro Radiology and the director of innovation deployment for AI at Radiology Partners, outlined a five-step AI model validation process designed to assess medical imaging tools effectively.

"If we want our radiologists to be excited about an AI tool and to engage with it, we ought to measure things that are relevant to them. And so the real purpose of this five-step process was to look at these AI models through the lens of a radiologist, because value is in their eyes. We focus on trying to generate some metrics that might predict whether they'll like an AI tool, whether they'll use it and whether they'll get the most value out of it so that patients benefit, so health systems actually get value out of these tools," Poff explained.

He said practices and hospitals that do not do this type of critical AI evaluation often find the radiologists do not use the products once they are implemented.

Poff spoke with Health Imaging at the Radiological Society of North America (RSNA) 2024.