An AI decision aid significantly improved decision quality, level of shared decision-making, patient satisfaction and functional outcomes in patients compared to an education-only approach, according to a new study in JAMA.

The reported exploration to sell Watson Health, the AI-driven health business of IBM, underscores deep challenges with technology in solving healthcare problems, according to the Wall Street Journal.

Only two of 34 representative studies evaluating the use of AI for real-world shared clinical decisionmaking from 2014 to 2020 included external validation of the models up for consideration.

Healthcare AI is advancing too quickly for its users to fully comprehend the implications of its design, development and applications, according to bioethics specialists who scanned the literature. 

AI-based CDS tools that perform well in clinical trials will flounder on the way to clinical practice if they’re not evaluated early and thoroughly for their effects on real-world clinical decisionmaking.  

One turnoff is remote food monitoring. Another is real-time feedback—whether from a live healthcare professional or an AI algorithm.

A noted AI researcher and educator who was drawn to the field by its escalating penetration of “the mysteries of perception and cognition” has found a sort of missing link in its evolution. 

Researchers have used explainable AI to break down a hypothetical animal’s foraging behaviors into measurable cognitive dynamics. They hope their success leads to a better understanding of how humans think.