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.

The predictive model can help physicians find a more intelligent, personalized approach for treating hypertension.

A top attractor of investors interested in medical imaging AI has drawn in a fresh $110 million.

Encouragingly, the MRI scans did not require the latest equipment advances and were conducted on a standard machine that is readily available at most hospitals—a 1.5 Tesla.