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Why Google could be essential to prediction in healthcare

The University of Chicago Medicine recently announced a collaboration with Google that will be directed towards studying the ways in which data obtained from electronic medical records can improve healthcare quality. Ultimately, UChicago Medicine hopes to reduce hospital readmissions and save lives by using new machine-learning techniques for predictive modeling.

Electronic Health Record (EHR) data, like X-rays or doctors’ notes, are currently not being utilized as effectively as possible. There is an abundance of data accumulating from routine hospital visits that can be used for machine-learning and eventually, predictive modeling. With the assistance of Google, UChicago Medicine hopes to create predictive algorithms associated with images and free text from EHRs to predict hospitalizations and identify instances where a patient’s health is declining.

Since Google provides such a unique contribution to improving healthcare worldwide, they plan on utilizing their expertise in analytics and growing their healthcare partnerships to make a lasting impact.

Stanford and the University of California, San Francisco, are currently in working collaborations with Google’s machine-learning research team. 

For additional information, access the following resources:

http://www.beckershospitalreview.com/healthcare-information-technology/uchicago-medicine-joins-google-effort-to-reduce-readmissions-with-ai-ehrs.html

https://sciencelife.uchospitals.edu/2017/05/17/uchicago-medicine-collaborates-with-google-to-use-machine-learning-for-better-health-care/

Photo: Google logo. Digital Image. Fine Print, Inc. 1 August  2014. Web. 25 May 2017. <fineprintnyc.com>.

 

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