Aided by augmented reality, AI and portable neuroimaging technology, physicians may soon be able to tease out images of patients’ brains—right there in the doctor’s office—to see how much pain each patient is suffering.

Healthcare AI isn’t yet good enough to reliably deliver on its promises where it stands to make the biggest difference—and it doesn’t have enough high-quality data to get there anytime soon.

Only one-fifth of consumers would trust healthcare advice from AI-generated communications, according to a recent poll.

The Massachusetts Medical Society, which publishes the New England Journal of Medicine, on June 19 named Eric J. Rubin, MD, PhD, as the newest editor-in-chief of the Journal and NEJM Group.

An initial set of studies went up this week at medRxiv, a new and somewhat controversial online outlet hosting preprinted clinical research reports—they haven’t yet been subject to peer review, much less journal editing—and the batch includes one dealing with AI.

Eyesight researchers have developed a machine-learning architecture whose best model, an ensemble classifier, achieved 93.4% accuracy in separating good candidates for corneal refractive surgery from patients likely to have post-surgery complications or poor outcomes.

AI is enabling healthcare workers to understand people’s moods with a level of accuracy that may be as unnerving as it is exciting.

Following total hip replacement, patients are well-served with AI-powered biofeedback that helps them rehab safely and effectively at home with occasional monitoring by a remote physical therapist.