We developed and evaluated a pipeline combining Mistral Large LLM and a postprocessing phase. The pipeline's performance was assessed both at document and patient levels. For evaluation, two data sets ...

Medical free texts such as pathology reports contain valuable clinical data but are challenging to structure at scale. Traditional natural language processing approaches require extensive annotated ...

Our Privacy, Cyber & Data Strategy Team explores key changes to UK data protection rules introduced by the Data (Use and Access) Act 2025 and provides a checklist of ...

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 ...

Abstract: To apply for higher education and job opportunities, a student's marksheet serves as a reference document. The conventional way of manually extracting meaningful information for companies ...

Note The agentic-doc Python library is now legacy. Please migrate to the new landingai-ade library, which is now the official Python library for Agentic Document Extraction and supports our newer API ...

Design and implement an end-to-end ETL (Extract, Transform, Load) pipeline using SQL for data extraction and transformation, and Python for orchestration and automation. Use any open dataset (e.g., ...

LinkedIn Is Using More User Data Than Ever to Train Its AI. Here's How to Opt Out As of Nov. 3, LinkedIn is now using data from members in the EU, EEA, Switzerland, Canada, and Hong Kong to train its ...

Credit: Image generated by VentureBeat with FLUX-pro-1.1-ultra A quiet revolution is reshaping enterprise data engineering. Python developers are building production data pipelines in minutes using ...