Leaders of the venture, dubbed “Project Amber,” are open-sourcing their technology and findings in the hope that other mental health researchers can take things from here.

A little more than a year after inking a 10-year pact on digital healthcare development, Mayo Clinic and Google Health have launched their first major research project together. Interestingly, it directly involves AI.

The bytes are accumulating far too fast for any human effort to connect whatever dots might be hiding in the massive muddle. Enter 40 researchers at 11 sites armed with AI and almost $18 million in new NIH funding.

Analyzing the scientific literature on medical AI published over the past 46 years, researchers in the U.K. have found the U.S. far ahead of the field for sheer quantity.

The FDA has greenlit a European company’s AI software package designed to streamline workflow for radiologists reading prostate MRIs.

Google Health all but invited the blowback when its AI developer-researchers suggested their breast-cancer model may be superior to radiologists’ eyes and generalizable across differing demographics.

If big data is to fulfill its potential for advancing the state of modern healthcare, developers of medical AI must be willing to show their work. 

Low-back imaging and interventions are often named among healthcare’s iffiest expenses due to the hit-or-miss predictability of the outcomes.