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.

A healthcare AI company has spotted several unexpected, off-label drug combinations that may do the job against COVID-19. In any case, the company is offering its complete AI toolkit free of charge to drug developers working on COVID treatments.

When Windy City residents send out tweets containing the term “food poisoning,” an algorithm offers a form for sharing details with Chicago’s public-health officials. Why not do the same with keywords like “cough,” “fever” and “trouble breathing” to help track COVID-19?

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).

Stanford researchers have developed a way to screen for lung cancer by combining next-gen molecular DNA quantification with machine learning. The experimental technique requires only a blood test and could, with refinement, replace low-dose CT scanning as an initial exam for longtime smokers.

Telehealth is having a moment in the sun as a possible answer to help mitigate the spread of the coronavirus by limiting exposure risks to patients and healthcare professionals.

Scripps Research is recruiting volunteers to contribute anonymized data on their resting heart rate and, optionally, to report signs of viral illness like fever or coughing.