Medical care is estimated to account for only 10-20% of healthcare outcomes. As a result, healthcare executives who wish to deliver high-quality care have to consider other elements that impact ...

Unstructured data, the deep, dark data that’s prevalent across the enterprise, but not always transparent or usable, continues to be a top business challenge. Data that lacks a predefined data model ...

Unstructured data refers to information that does not have a predefined data model or organized format, making it more challenging to store, process, and analyze compared to structured data. Unlike ...

Clinical-grade, expert-supported natural language processing (NLP) is valuable to payers and providers when exchanging patient information through continuity-of-care documents. One of the most ...

Developers and data scientists use generative AI and large language models (LLMs) to query volumes of documents and unstructured data. Open source LLMs, including Dolly 2.0, EleutherAI Pythia, Meta AI ...

Expertise from Forbes Councils members, operated under license. Opinions expressed are those of the author. By 2020, U.S. healthcare data had reached 2,314 exabytes—15 times more than in 2013—thanks ...

The new Centers for Medicare & Medicaid Services Interoperability and Patient Access final rule requires the interoperability of full-text medical records. "The Interoperability and Patient Access ...

Forbes contributors publish independent expert analyses and insights. I track enterprise software application development & data management. Information, without order, is chaotic. Attempting to work ...

Data scientists today face a perfect storm: an explosion of inconsistent, unstructured, multimodal data scattered across silos – and mounting pressure to turn it into accessible, AI-ready insights.