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Artificial intelligence approaches using natural language processing to advance EHR-based clinical research.

Authors
  • Juhn, Young1
  • Liu, Hongfang2
  • 1 Precision Population Science Lab, Division of Community Pediatric and Adolescent Medicine, Department of Pediatric and Adolescent Medicine, Rochester, Minn; Division of Allergy, Department of Medicine, Mayo Clinic, Rochester, Minn. Electronic address: [email protected]
  • 2 Division of Digital Health, Department of Health Sciences Research, Mayo Clinic, Rochester, Minn.
Type
Published Article
Journal
The Journal of allergy and clinical immunology
Publication Date
Feb 01, 2020
Volume
145
Issue
2
Pages
463–469
Identifiers
DOI: 10.1016/j.jaci.2019.12.897
PMID: 31883846
Source
Medline
Keywords
Language
English
License
Unknown

Abstract

The wide adoption of electronic health record systems in health care generates big real-world data that open new venues to conduct clinical research. As a large amount of valuable clinical information is locked in clinical narratives, natural language processing techniques as an artificial intelligence approach have been leveraged to extract information from clinical narratives in electronic health records. This capability of natural language processing 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 electronic health record data for clinical research concerning allergy, asthma, and immunology and highlights the potential, challenges, and implications of natural language processing techniques. Copyright © 2019 American Academy of Allergy, Asthma & Immunology. Published by Elsevier Inc. All rights reserved.

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