Google’s AI division is eager to break into healthcare, and with ‘Medical Brain’ they might be successful. First is harnessing the voice recognition used in their Home, Assistant, and Translate products. Last year they started to test a digital scribe with Stanford Medicine to help doctors automatically fill out EHRs from patient visits, which will conclude in August. Next up, and staffing up, is a “next gen clinical visit experience” which uses audio and touch technologies to improve the accuracy and availability of care.
The third is research Google published last month on using neural networks to predict how long people may stay in hospitals, their odds of re-admission and chances they will soon die. The neural net gathers up the previously ungatherable–old charts, PDF–and transforms it into useful information. They are currently working with the University of California, San Francisco, and the University of Chicago with 46 billion pieces of anonymous patient data.
A successful test of the approach involved a woman with late-stage breast cancer. Based on her vital signs–for instance, her lungs were filling with fluid–the hospital’s own analytics indicated that there was a 9.3 percent chance she would die during her stay. Google used over 175,000 data points they saw about her and came up with a far higher risk: 19.9 percent. She died shortly after.
Using AI to crunch massive amounts of data is an approach that has been tried by IBM Watson in healthcare with limited success. Augmedix, Microsoft, and Amazon are also attempting AI-assisted systems for scribing and voice recognition in offices. CNBC, Bloomberg