Progress has been made in healthcare with improving data interoperability, or "data liquidity," the ability of data to securely flow from one place to another, as needed and appropriate, for patient ...

First, institutions must ensure that synthetic datasets are continuously recalibrated against fresh, real-world evidence. The ...

If your AI feels slow, expensive or risky, the problem isn’t the models — it’s the data, and cognitive data architecture is ...

Although federal EHR technology investments had disappointing results, they were necessary to start digitizing the nation's health care data and set the stage for a promising future. An architecture ...

For decades, enterprise data infrastructure focused on answering the question: “What happened in our business?” Business intelligence tools, data warehouses, and pipelines were built to surface ...

Rajiv Shesh is the Chief Revenue Officer at HCLSoftware where he leads revenue growth & customer advocacy for Products & Platforms division. What’s really powering AI? High-quality data—foundational ...

The biggest challenge to AI initiatives is the data they rely on. More powerful computing and higher-capacity storage at lower cost has created a flood of information, and not all of it is clean. It ...

Overview: Healthcare data analysts turn patient and hospital data into useful insights.Strong demand exists as hospitals rely more on digital records.Skills in ...