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Ency department computerized medical records for intra-hospital syndromic surveillance Solweig Gerbier1,2*, Olga Yarovaya2, Quentin Gicquel2, Anne-Laure Millet3, V ronique Smaldore3, V ronique Pagliaroli4, Stefan Darmoni5 and Marie-H l ne Metzger1,2 Abstract Background: The identification of patients who pose an epidemic hazard when they are admitted to a health facility plays a role in preventing the risk of hospital acquired infection. An automated clinical decision support system to dete.
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Biomedcentral FAQ
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Supporting doctors in decision making NLP solutions can also analyze clinical documents and support physicians in real-time decision making. For instance, after analyzing doctor notes, the system can predict hospital bed demands, which gives hospital staff time to prepare and accommodate incoming patients.
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Clinical natural language processing (NLP), also known as Medical NLP, Health NLP, or Biomedical NLP, refers to automated methods to manipulate human language (i.e., spoken or textual narratives) in the biomedical domain, ranging from natural language understanding to natural language generation tasks.
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Natural language processing (NLP) technologies provide a potential solution, as these tools can help care teams and researchers sift through mountains of data and generate meaningful insights for applications in population health management and clinical decision support.
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Clinical natural language processing (NLP), also known as Medical NLP, Health NLP, or Biomedical NLP, refers to automated methods to manipulate human language (i.e., spoken or textual narratives) in the biomedical domain, ranging from natural language understanding to natural language generation tasks.
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Healthcare natural language processing uses specialized engines capable of scrubbing large sets of unstructured data to discover previously missed or improperly coded patient conditions.
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Clinical NLP automates the extraction of pertinent information from clinical notes. This accelerates data retrieval, enabling clinicians to efficiently access critical insights without manually sifting through lengthy narratives.
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The future of natural language processing (NLP) for electronic health records (EHRs) is bright. NLP is a rapidly developing field with the potential to revolutionize the way healthcare is delivered. NLP can be used to extract insights from EHRs that would otherwise be difficult or impossible to obtain.
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