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.

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).

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.

The coronavirus crisis continues to unite heretofore unaffiliated technology powerhouses at the forefront of AI and other forms of IT innovation in healthcare. The trend continued March 26 with the launch of a multifaceted, far-flung and very well-funded institute.

Researchers at the University of Waterloo in Ontario have introduced a convolutional neural network for diagnosing COVID-19 on chest X-rays.

Two data scientists say they’ve created AI algorithms that can do in a week what biological researchers might otherwise spend years trying to pull off in a laboratory: discover antibody-based treatments that have a fighting chance to beat back COVID-19.

The can-do spirit of techies is shining around the world in some modest but mighty efforts to pitch in against the global coronavirus pandemic.

The tech sector is abuzz with high hopes in AI’s potential to help the world beat back COVID-19. A veteran writer who’s been on the high-tech beat for years offers a reality check.

Some look like people in robot costumes. Some look like microwave ovens on wheels. All helped healthcare workers in Wuhan, China, avoid contracting COVID-19 while caring for hospitalized patients who had the illness.