Glioma patients typically need a biopsy so physicians can make a treatment decision, but researchers have developed a new AI algorithm that could make such biopsies unnecessary. 

Sometimes there’s real progress behind the slick pitch.

With so many eyes fixed on New York City as the “epicenter” of the COVID-19 crisis in the U.S., it might go unnoticed at the national level that nearly 60,000 infections could be recorded some 150 miles to the north by June 8.

An AI-championing health-tech company whose name sounds like that of a consumer group has announced a formal partnership with the Big Tech corporation behind the AI-pioneering Watson technology.

Cleveland Clinic and the analytics software vendor SAS have jointly developed predictive models to help hospitals prepare for three COVID-19 scenarios—worst case, best case and most likely.

Microsoft has debuted a new AI solution that could help slow the spread of the new coronavirus.

A predictive algorithm has distinguished patients free of obstructive sleep apnea from those with three levels of the condition—mild, moderate and severe—with 91% accuracy. And it did so using only 3D photos of the subjects’ faces.

Using brain MRI and a deep learning network, researchers have achieved 97% accuracy at classifying a gene mutation indicative of growth in localized gliomas.

A deep-learning algorithm has accurately measured 26 pairs of uneven leg lengths on children’s x-rays at a rate 96 times faster than that recorded by an experienced, subspecialty-trained pediatric radiologist using manual means.

“In a pandemic of this magnitude, flexibility is paramount for a healthcare system under siege by COVID-19,” CMS Administrator Seema Verma said.