Communications Medicine (Apr 2022)

Personalized antibiograms for machine learning driven antibiotic selection

  • Conor K. Corbin,
  • Lillian Sung,
  • Arhana Chattopadhyay,
  • Morteza Noshad,
  • Amy Chang,
  • Stanley Deresinksi,
  • Michael Baiocchi,
  • Jonathan H. Chen

DOI
https://doi.org/10.1038/s43856-022-00094-8
Journal volume & issue
Vol. 2, no. 1
pp. 1 – 14

Abstract

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Corbin et al. train machine learning models on electronic health record data to predict susceptibility of infections to particular antibiotics (personalized antibiograms). Antibiotic selection driven by personalized antibiograms achieves similar coverage rates to those seen in actual clinical practice using fewer broad spectrum antibiotics.