MIT charts the encouraging story behind—and in front of—the National COVID Cohort Collaborative (N3C ).

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

Empathetic, affable, visually unthreatening and coolly competent in several healthcare tasks, a newly trained nurse named Grace has made a head-turning debut.

Many parents would let their children be read to by robots as long as the device didn’t project a little too much lifelikeness.

Because they learn as they go, machine learning models for drug discovery have to be continuously re-trained for changing conditions in drug production processes.

When the network interpreted complete videos from 42 consecutive patients, it boosted detection rates by as much as 50% over physician-alone reads.

The system hit 88% accuracy at optimizing stimulation settings, as confirmed by brain-response patterns on neuroimaging as well as visibly observable symptom improvement in patients with Parkinson’s disease.

Explainable AI is almost as sharp as human experts when the cause is simple and straightforward, as with ingestion of a single common cleaning product.

Bioengineers have developed a brain-computer interface that replicates the sense of touch, allowing a robotic arm and hand to not only receive command signals from the brain but also send back signals of stimulation.

Natural language processing of social media posts is useful for identifying depression, anxiety and suicidal thinking, but models trained on population data cannot discern long-term patterns in any one person’s state of mind.