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By building a Fast Healthcare Interoperability Resources (FHIR) database on Google Cloud, Nemati and Sharma are ensuring that the engine can scale and interoperate across institutions on a reliable, secure, and private platform that also integrates with other projects on cloud technologies, like the wearable monitoring devices already in use at Emory hospitals. Scaling through Google Cloud So far, Nemati, Sharma, and their team at Emory have partnered with the Emory eICU Center to validate the engine on data hosted on local servers, testing different time frames before achieving an impressive 85% accuracy at predicting sepsis four to six hours before onset. In order to deploy the program at other sites they turned to App Engine. "By converting our TensorFlow-based sepsis prediction algorithm into an App and running it on the Google App Engine, we were able to completely abstract away infrastructure requirements for running and scaling up the deployment and instead focus only on improving our algorithm, " Nemati asserts.
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