Use of Machine Learning to Assess the Management of Uncomplicated Urinary Tract Infection.

Journal: JAMA network open
PMID: 39888618

Abstract

IMPORTANCE: Uncomplicated urinary tract infection (UTI) is a common indication for outpatient antimicrobial therapy. National guidelines for the management of uncomplicated UTI were published in 2011, but the extent to which they align with current practices, patient diversity, and pathogen biology, all of which have evolved greatly in the time since their publication, is not fully known.

Authors

  • Noah Jones
    MIT Media Lab, Massachusetts Institute of Technology, Cambridge.
  • Ming-Chieh Shih
    College of Life Sciences and Medicine, National Tsing Hua University, Hsinchu, Taiwan.
  • Elizabeth Healey
    From the Department of Biomedical Informatics, Harvard Medical School (K.-H.Y., E.H., I.S.K., A.K.M.), the Department of Pathology, Brigham and Women's Hospital (K.-H.Y.), and the Harvard-MIT Division of Health Sciences and Technology (E.H.) - all in Boston; and the School of Computing, National University of Singapore, Singapore (T.-Y.L.).
  • Chen Wen Zhai
    Operations Research Center, Massachusetts Institute of Technology, Cambridge.
  • Sonali Advani
    Division of Infectious Diseases, Department of Medicine, Duke University School of Medicine, Durham, North Carolina.
  • Aaron Smith-McLallen
    4 Advanced Analytics, Independence Blue Cross , Philadelphia, Pennsylvania.
  • David Sontag
    1 Department of Computer Science, New York University , New York, New York.
  • Sanjat Kanjilal
    Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Healthcare Institute, Boston, Massachusetts.

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