Natural Language Processing to Identify Infants Aged 90 Days and Younger With Fevers Prior to Presentation.

Journal: Hospital pediatrics
PMID: 39679596

Abstract

OBJECTIVE: Natural language processing (NLP) can enhance research studies for febrile infants by more comprehensive cohort identification. We aimed to refine and validate an NLP algorithm to identify and extract quantified temperature measurements from infants aged 90 days and younger with fevers at home or clinics prior to emergency department (ED) visits.

Authors

  • Paul L Aronson
    Section of Pediatric Emergency Medicine, Departments of Pediatrics and of Emergency Medicine, Yale School of Medicine, New Haven, Connecticut.
  • Nathan Kuppermann
    Departments of Emergency Medicine and Pediatrics, University of California, Davis School of Medicine, Sacramento, CA.
  • Prashant Mahajan
    Department of Emergency Medicine, University of Michigan School of Medicine, Ann Arbor, USA.
  • Blake Nielsen
    Department of Pediatrics, University of Utah School of Medicine, Salt Lake City, Utah.
  • Cody S Olsen
    Department of Pediatrics, University of Utah School of Medicine, Salt Lake City, Utah.
  • Huong D Meeks
    Department of Pediatrics, University of Utah School of Medicine, Salt Lake City, Utah.
  • Robert W Grundmeier
    Department of Biomedical and Health Informatics, The Children's Hospital of Philadelphia, 3535 Market Street, Suite 1024, Philadelphia, PA, 19104, USA.

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