The deep learning models had nothing more to go on than routine abdominal CT scans acquired preoperatively.

With AI-inclusive devices routinely earning regulatory approval for use in clinical settings, the time seems ripe for helping technology translators talk above the din of visionary futurists.

Researchers have developed a nanopore that uses AI to detect COVID-19 and other viruses in easily obtained saliva specimens.

The authors concentrate on robotic technologies that either augment a surgeon’s movements or simplify a multistep process.

Many cases will be handled by primary-care providers, eye technicians and even patients themselves connected by telehealth and armed with commercial test kits and AI.

The data will draw on everything from census findings to driving habits gathered from vehicle sensors to—arguably most consequentially—medical records.

Working with 9/11 responders as retrospective subjects, researchers in mental health and computer science have shown AI language tools can help predict the course of PTSD.

Comparing four methods for predicting septic shock in children hospitalized with sepsis, Johns Hopkins researchers have found a newer machine-learning approach superior to an older one as well as to two conventional methods.