An experimental set of algorithms has achieved accuracy of 70% to 80% at predicting which of 53 COVID-positive patients at two hospitals in China would get the sickest.

Researchers in the U.K. and U.S. have developed an automatic prediction model that can tell if someone is infected with COVID-19 based on symptoms alone.

AI developers working to refine COVID-19 detection in chest x-rays must navigate two unavoidable speed bumps.

The FDA has cleared an investor-backed teleradiology provider to market two AI algorithms the company developed to flag certain stroke-associated findings in images from head CT scans.

A disease that hits most people mildly but some very hard—and so wreaks havoc with its unpredictability among the infected—would seem a good target for AI’s predictive prowess.

Researchers in South Korea have shown that AI trained on photos of both Asian and Caucasian patients can help dermatologists more accurately diagnose many diseases and disorders of the skin in both subpopulations.

The Finnish maker of the Oura health-tracking finger ring is sponsoring a two-pronged, AI-aided COVID-19 study at the University of California, San Francisco (UCSF).

The idea is to initially place the device in medical waiting areas, from where it would help prepare staff for caseload ebbs and flows. Later it might be set in larger public spaces, helping to monitor epidemiological trends at the population level.

Pharmaceutical giant Eli Lilly has partnered with AbCellera Biologics, a biotechnology company based in Canada, to address the new coronavirus crisis by developing antibody products to treat and prevent the virus.

Another healthcare company is leveraging AI to address the new coronavirus pandemic and help identify potential patients who could have the virus.

As the U.S. continues ramping up its response to the new coronavirus, COVID-19, the role of AI could loom large in helping identify the highest risk patients.

AI could provide radiologists with significant value as an advanced peer review tool, according to new findings published in Academic Radiology.