Amazon fuels Harvard hospital's machine learning research program
Amazon thinks the cloud can make hospitals run better.
The company’s Amazon Web Services unit is sponsoring a program at Harvard’s Beth Israel Deaconess Medical Center (BIDMC) that applies machine learning to improve hospital efficiency. The initiative will focus on clinical care, operations and waste reduction, which Amazon said will ultimately improve patient care.
The Amazon grant will supply as much as $2 million to machine learning research, Bloomberg reported.
“Every minute spent on cumbersome clerical tasks and management adds up to millions in lost productivity and directly impacts patient care,” Dr. John Halamka, executive director of the Health Technology Exploration Center at Beth Israel Deaconess Medical Center, said in a statement.
This is yet another push by Amazon into health, where it is in fierce competition with fellow tech giants Microsoft, Apple and Google. Late last year, the company’s cloud division unveiled a service to mine and decode medical records called Amazon Comprehend Medical.
The Harvard learning hospital is going after the boring stuff first. Two ongoing projects that aim to improve operating room scheduling and document management can save the hospital staff time and help avoid errors and delays, Amazon said.
Another project is working to identify which patients are likely to skip an appointment and send them reminders. In the future, BIDMC will use machine learning to predict when the hospital can expect high volumes of incoming patients and where there might be free space.
The Boston-based hospital is using tools like Amazon SageMaker, Amazon Comprehend Medical, Apache MXNet and Tensorflow, which are hosted in on AWS.
“BIDMC’s innovations using AWS machine learning services like Amazon SageMaker will ultimately pave the way for other healthcare providers to save lives and reduce costs for patients nationwide,” said Swami Sivasubramanian, VP of machine learning at AWS.
This article was written by James Thorne and orginially appeared on GeekWire.
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