Radiology makes up the vast majority of FDA-cleared AI algorithms, but with minimal or no reimbursement, hospital administrators may ask whether AI’s value justifies its expense.

Overall, cardiologists made corrections to 16.8% of AI-generated assessments and 27.2% of sonographer assessments.

A popular marketer of handheld ultrasound devices has won FDA approval for an AI-enabled B-line quantification tool for use with patients suspected of having compromised lung function.

When used to flag anomalies in combined chest and musculoskeletal X-rays, imaging AI can relieve overstretched emergency radiology teams.

The FDA has OK’d a new artificial intelligence platform for quickly diagnosing stroke on unenhanced CT scans.

Using CT scans, a deep learning algorithm can recommend optimal lung cancer screening intervals by distinguishing between high-risk and low-risk lung nodules. 

AI-powered analysis can now assess cognitive decline by noting gaps in chronological versus biological “brain age.”

A commercially available AI package has proven adept at distinguishing between two closely similar but unequally urgent conditions on chest X-rays.