The capability could allow immediate alerting of CT technologists, who would adjust scan protocols or re-scan patients to optimize image quality prior to physician interpretation.

Radiologists across Europe have been finding AI algorithms useful for improving efficiency at some tasks—yet, overall, few have received AI-attributable workload relief.

A small medtech outfit in North Carolina is opening its trove of medical imaging datasets to academic researchers working to develop AI applications for healthcare.

There’s no shortage of educational resources for teaching radiologists at all learning levels the principles and particulars of medical AI, but the need for radiology-specific materials is pronounced, according to a study published June 23. 

In a sampling of 2,273 chest radiographs of kids aged 2 to 18-years-old the AI-based software achieved diagnostic accuracies ranging from 86% to 96.9% for detecting a myriad of pathologies.

A healthcare AI platform supplier headquartered in Scotland is collaborating on marketing with a San Francisco-based AI startup co-founded and -led by a radiologist.

The model performed well in assessing treatment responses, but experts explained that one of the most beneficial aspects of their model was that its results are interpretable in a “clinician-friendly way.” 

"Our model is a potential tool to improve the primary trisomy 21 screening based on ultrasonographic images for universal clinical application," experts involved in the study suggested.