Natural language processing to advance EHR-based clinical research in Allergy, Asthma, and Immunology.

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ID: 85154
2019
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Abstract
The wide adoption of electronic health record systems (EHRs) in health care generates big real-world data that opens new venues to conduct clinical research. As a large amount of valuable clinical information is locked in clinical narratives, natural language processing (NLP) techniques as an artificial intelligence approach have been leveraged to extract information from clinical narratives in EHRs. This capability of NLP potentially enables automated chart review for identifying patients with distinctive clinical characteristics in clinical care and reduces methodological heterogeneity in defining phenotype obscuring biological heterogeneity in research concerning allergy, asthma, and immunology. This brief review discusses the current literature on the secondary use of EHR data for clinical research concerning allergy, asthma, and immunology and highlights the potential, challenges, and implications of NLP techniques.
Reference Key
juhn2019naturalthe Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Juhn, Young;Liu, Hongfang;
Journal the journal of allergy and clinical immunology
Year 2019
DOI
S0091-6749(19)32604-1
URL
Keywords
artificial intelligence Machine learning Data mining asthma allergy natural language processing informatics immunology algorithms ehrs

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