Derivation of a natural language processing algorithm to identify febrile infants.

Journal: Journal of hospital medicine
Published Date: Jan 1, 2022

Abstract

BACKGROUND: Diagnostic codes can retrospectively identify samples of febrile infants, but sensitivity is low, resulting in many febrile infants eluding detection. To ensure study samples are representative, an improved approach is needed.

Authors

  • Jeffrey P Yaeger
    Department of Pediatrics, University of Rochester Medical Center, Rochester, New York, USA.
  • Jiahao Lu
    Department of Pediatrics, University of Rochester Medical Center, Rochester, New York, USA.
  • Jeremiah Jones
    Department of Biostatistics and Computational Biology, University of Rochester Medical Center, Rochester, New York, USA.
  • Ashkan Ertefaie
    Department of Biostatistics and Computational Biology, University of Rochester, Rochester, New York, USA.
  • Kevin Fiscella
    Department of Family Medicine, University of Rochester Medical Center, Rochester, New York, USA.
  • Daniel Gildea
    Department of Computer Science, University of Rochester, Rochester, New York, USA.

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