Scaling for the future of ophthalmology with artificial intelligence powered by Azure Healthcare API

Regular Contributor

Written by Heather Jordan Cartwright, Vice President, Microsoft Health and LifeSciences

 

Disconnected medical data sets are everywhere. Particularly in the imaging segment, the growth in the number of devices, data size, and types of data being captured is breaking the traditional systems for managing data on-premises. Many companies are turning to the cloud for scale, but the smart ones are choosing purpose-built health technology that goes beyond just pushing data to a lake for storage or consolidation. Leaders in the imaging industry like ZEISS are focused on innovation that’s purpose-built for healthcare, choosing cloud technology that allows for interoperability to connect and exchange data in the cloud through open standards to enable scalability for the future of AI.

 

As one of the world’s largest providers of ophthalmology devices and software, ZEISS manages one of the broadest imaging device footprints in the world. Dominated by thousands of boutique clinics, data in ophthalmology is siloed, un-shareable, and often captured in such small amounts that at first pass it looks virtually unusable for AI and machine learning. But as ZEISS embraced the cloud, they sought to build a system that would allow them to not only bring DICOM data to the cloud but to make it easier to generate insights for predictive and preventative care with that data. In the process, they found that focusing on data interoperability in the cloud is now opening the doors to enable improved patient outcomes and research new treatment processes.

 

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