A data analytics system implemented via a back-end application computer server, comprising: (a) a first risk relationship data store containing electronic records that represent a plurality of risk ...

In this special guest feature, Elaine Wang, CEO of MCoreLab, discusses the key platform requirements and architectural considerations for real-time big data analytics, and provide insights from best ...

High reliability applications in service-critical markets, such as autonomous driving and cloud computing, demand maximum performance and minimal power and cost. Reducing design margins while ...

AI is reducing manual data work, allowing engineers to focus on system design and reliability. Real-time and cloud-based data ...

Overview Data science roles are expanding as AI tools handle more routine work.Foundation models are replacing task-by-task ...

As we are in the process of hyperscaling the large volumes of data that our devices and sensors create, processing this data along the way at far and near edges, and transmitting the hard-to-imagine ...

Consistency Between State's Cancer Registry and All-Payer Claims Database in Documented Radiation Therapy Among Patients Who Received Breast Conservative Surgery Data from six hospital information ...

With increased mergers and acquisitions, hospitals, hospital systems and Integrated Delivery Networks face significant challenges to aggregate and compare colossal datasets, identify problems, and ...

The ability to analyze ever-growing volumes of data – data that’s increasingly spread across hybrid-cloud and multi-cloud systems – is critical for businesses to remain competitive today. Here are 10 ...