A multinational group of scholars has put together two fresh sets of guidelines for researchers testing AI applications in clinical trials.

Researchers in Canada are working to develop AI models for diagnosing and treating mental illness. One application in their sights involves automated interpretations of brain scans.

When a virus mutates, the researchers explained, it can be benign or even make the virus less dangerous to humans. In this instance, however, many detected mutations have a significant chance of becoming more infectious strains of COVID-19.

Computerized clinical decision support has strong upsides and few to no downsides for both clinicians and patients, according to a systematic literature review. 

Concepts from the art and science of deep learning for medical practice can inform those employed in the art and science of medical education.

Medical journals accepting reprint fees are much more likely to publish articles written by authors who received industry payments.

Whatever name it takes when it goes down in history, the present “information age” will be inextricably linked to AI. It’s been so since around 2008, although popular perception needed time to catch up with the depth of the development.

Patient-facing healthcare workers are neither softened nor hardened in their attitudes toward clinical decision support powered by AI when it’s instead called “AHI,” for augmented human intelligence.

An AI system trained to supply clinical decision support in the U.S. has proven adaptable for physicians treating patients with lung cancer on the other side of the globe.

Asked to identify which of six fictional persons is most likely to be a terrorist, 85% of 1,500 participants in a psychology experiment selected one of the least likely suspects. And they did so specifically because they’d seen an AI robot make the ridiculous choice first.