Where Google is applying machine learning, predictive analytics in healthcare

Google Cloud launched its healthcare API in April and has big plans for the future, according to Joe Corkery, director of product management, healthcare and life sciences at Google Cloud.

He told Tech Republic that the application was built to enable interoperability and is focused on sharing medical records and digital images. It supports Health Level Seven International, version two and Fast Healthcare Interoperability Resources standards for healthcare data.

"We've invested heavily in making sure that we are building our applications to meet those standards, and then building out tools that allow our customers and partners to take the different flavors of those standards that they might have, or their own data, and build ingestion pipelines where they can do the data transformation that's required to convert that data into the open standards," he said.

Mr. Corkery also mentioned that Google is "in the early stages of applying machine learning to healthcare" and sees potential in applications for medical imaging, diagnostics for diabetic retinopathy, and predictive analytics based on medical records data. He said customers are particularly interested in using predictive analytics to project whether patients have sepsis earlier as well as predicting breast cancer recurrence based on medical records and imaging.

Another area of focus is helping healthcare organizations bring patient data together, even when they move between hospitals and health systems.

"One of the things that we're really trying to do right now is help organizations build this data platform on top of which they can bring together the data around their different patient populations, so they can have this longitudinal view of the patients in their population," he said. He also mentioned giving healthcare organizations and researchers access to more de-identified data to make better prediction models.

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