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Google Is Training Machines To Predict When a Patient Will Die (bloomberg.com)
A newly developed tool by Google can forecast a host of patient outcomes, including how long people may stay in hospitals, their odds of re-admission and chances they will soon die. Google documented some of this tool's abilities in May; in one instance, Google's tool estimated, by taking 175,639 data points into consideration, that a particular patient's odds at dying during her stay at the hospital was 19.9 percent, up from 9.3 percent that the hospital's computers had estimated. Now Bloomberg reports what Google intends to do with this new tool next. From the report: Google's next step is moving this predictive system into clinics, AI chief Jeff Dean told Bloomberg News in May. Dean's health research unit -- sometimes referred to as Medical Brain -- is working on a slew of AI tools that can predict symptoms and disease with a level of accuracy that is being met with hope as well as alarm. Inside the company, there's a lot of excitement about the initiative.
"They've finally found a new application for AI that has commercial promise," one Googler says. Since Alphabet's Google declared itself an "AI-first" company in 2016, much of its work in this area has gone to improve existing internet services. The advances coming from the Medical Brain team give Google the chance to break into a brand new market -- something co-founders Larry Page and Sergey Brin have tried over and over again. Software in health care is largely coded by hand these days. In contrast, Google's approach, where machines learn to parse data on their own, "can just leapfrog everything else," said Vik Bajaj, a former executive at Verily, an Alphabet health-care arm, and managing director of investment firm Foresite Capital. "They understand what problems are worth solving," he said. "They've now done enough small experiments to know exactly what the fruitful directions are." The report adds that, among other things, Google's tool has the ability to sift through notes buried in PDFs or scribbled on old charts.
"They've finally found a new application for AI that has commercial promise," one Googler says. Since Alphabet's Google declared itself an "AI-first" company in 2016, much of its work in this area has gone to improve existing internet services. The advances coming from the Medical Brain team give Google the chance to break into a brand new market -- something co-founders Larry Page and Sergey Brin have tried over and over again. Software in health care is largely coded by hand these days. In contrast, Google's approach, where machines learn to parse data on their own, "can just leapfrog everything else," said Vik Bajaj, a former executive at Verily, an Alphabet health-care arm, and managing director of investment firm Foresite Capital. "They understand what problems are worth solving," he said. "They've now done enough small experiments to know exactly what the fruitful directions are." The report adds that, among other things, Google's tool has the ability to sift through notes buried in PDFs or scribbled on old charts.
Here's the problem: how does one avoid a bad feedback loop? i.e. Computer predicts patient is likely to die, so doctors spend less time attempting to work the problem and/or shift the patient into a palliative care pathway. By predicting that a patient is likely to die, the computer will have made that patient EVEN MORE likely to die.