GeekWire
JUNE 22, 2023
DexCare, led by CEO Derek Streat, just landed $75 million to advance the development of its healthcare patient demand and access platform. DexCare Photo) Derek Streat , CEO of the fast-growing healthcare patient demand and access platform DexCare, is a startup veteran with 25 years of experience under his belt. Keeping up with demand.
Cloud Musings
DECEMBER 11, 2015
An example of the advantage that Teradata PaaS can bring to your business is a rapidly growing US healthcare provider that needed to sustain their unpredictable growth in a rapidly expanding business. To successfully overcome this dilemma, the company adopted Teradata PaaS through the use of the managed cloud services model.
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CTOvision
JUNE 7, 2014
Healthcare : Think of medical devices and how they’ve progressed – pin pricks for testing blood sugar to diabetes pumps to contact lenses that can monitor your blood sugar. You can opt-in to smart metering so that a utility can load balance energy distribution. Here are some examples….
CTOvision
FEBRUARY 24, 2014
Clients across a variety of industries, including gaming, financial services, mobile device manufacturers, online learning, retail and healthcare are already using Cloudant technology. Financial terms were not disclosed.
CIO Business Intelligence
FEBRUARY 27, 2024
Enhanced call routing: TFS can kick emergency response into high gear with the ability to intelligently route calls based on location, load balancing, and other factors. In 2019, we made history by conducting the first-ever NG9-1-1 test call using a commercially available system in Canada.
Scott Lowe
SEPTEMBER 1, 2015
Casado starts his discussion about how the application has changed—the application is now a combination of servers, clients, load balancers, firewalls, and storage repositories. Connectivity changes how education, healthcare, and other areas are implemented, managed, and delivered to citizens. devices connected per person to 2.9
Dataconomy
MAY 22, 2023
Here are a few examples: Healthcare: Distributed learning has been employed to train models on distributed medical data while maintaining patient privacy, enabling collaborative research and improving diagnostic accuracy. As the number of machines or nodes increases, coordinating and synchronizing the training process becomes more complex.
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