Adding context to data has been a goal for enterprise communications – especially in the customer experience – for over a decade. Data without context is fragmented, which means it cannot be used to ...

Organizations have a wealth of unstructured data that most AI models can’t yet read. Preparing and contextualizing this data is essential for moving from AI experiments to measurable results. In ...

Extract data and apply schemas across your multi-modal content, with confidence scoring and user validation enabling greater speed of data ingestion. Process claims, invoices, contracts and other ...

Background: Preventive cardiology relies on a comprehensive view of patient health, including biomarkers and imaging findings. However, critical data, such as coronary calcium scores (CCS) and ...

Abstract: Exponential growth of unstructured data in the form of text documents, emails, and web content presents a noticeable challenge to automated data extraction. This kind of data has much more ...

The final, formatted version of the article will be published soon. Background and objective. Structured clinical data is essential for research and informed decision-making, yet medical reports are ...

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What if the messy, unstructured text clogging your workflows could be transformed into a goldmine of actionable insights? Imagine sifting through mountains of customer reviews, clinical notes, or news ...