One turnoff is remote food monitoring. Another is real-time feedback—whether from a live healthcare professional or an AI algorithm.

The tools could be used by primary care providers to head off adverse respiratory events and suboptimal healthcare utilization. 

An AI application that interprets MRI scans of the brain for signs or confirmation of injury has received 510(k) clearance from the FDA.

Researchers have found that some AI models do better, on average, than expert psychiatrists at the difficult task.

The FDA has cleared UK-based Ultromics to sell an AI-powered tool for diagnosing coronary artery disease (CAD) on echocardiograms.

Gastroenterologists need not fear being replaced by machines—and patients don’t have to worry about robot colonoscopists.

Detecting diabetic retinopathy on eyeball imaging has been touted as one of medical AI’s most promising applications, as “the machine” has repeatedly equaled or bested humans at the task.

Academic experts in disaster response have developed an AI-based simulation model that accurately predicts ebbs and flows in traffic at drive-through vaccination stations.

Now comes a boomlet in vendors looking to piggyback on Viz.ai’s success, according to Niall Brennan, MPP, a member of Viz.ai’s advisory board who is also the head of the Healthcare Cost Institute.

A new deep learning algorithm quickly and accurately forecasts outcomes of COVID-positive patients in the ER going by routine workup information.

Oxford researchers have developed and prospectively validated two AI tools that can quickly screen hospital patients for COVID-19 using routine clinical data.

Various scenarios within medical diagnostics are among the AI use cases that an official European watchdog has flagged as a potential source of hazards to fundamental human rights.