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

Researchers at New York University have demonstrated an AI-based way to send COVID patients from the ER to the most appropriate care setting according to their individualized risk.  

As its techniques and technologies mature, medical AI will increasingly be used to predict the health trajectories of both outpatients and inpatients. But how will it do at converting educated projections into preventative care?

One of the nastiest aspects of the COVID crisis is its possible setting of the stage for one or more pandemics to follow. The risk of such a scenario is heightened by the rate at which moms and dads are avoiding the pediatrician for routine vaccinations.

Health and Human Services will award up to five grants as part of the program, with a Sept. 1 application deadline. 

Industry researchers in medical AI have demonstrated a “causal reasoning” algorithm whose diagnostic accuracy would place it among the top 25% of primary care doctors in the U.K. 

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

Someone had to come right out and ask. Six researchers representing four medical specialties have done so, weighing the odds by reviewing a representative sample of the literature.