Catch up on the top radiology content of the past week.

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?

In the first of a two-part podcast episode, Lauren Nicola, MD, Christoph Wald, MD, PhD, MBA, and Peter Shen discuss current challenges with reimbursement for AI in radiology.

A deep learning model developed for predicting BI-RADS assessments from dynamic contrast-enhanced (DCE) breast MRI had over a 14 percent lower AUC than radiologist evaluation in external validation testing.

While better imaging may reduce the need for additional diagnostic tests, it may also eliminate the reimbursement that comes with those additional tests.

The CARE Chest X-Ray (CXR) Triage software reportedly bolsters consistent flagging of suspicious chest X-rays for lung collapse and pneumomediastinum across reviewing readers of different experience levels.