Using machine learning to predict antibiotic resistance to support optimal empiric treatment of urinary tract infections

• Main Authors: Ben Brintz (Author), McKenna Nevers (Author), Matthew Goetz (Author), Kelly Echevarria (Author), Karl Madaras-Kelly (Author), Matthew Samore (Author)
• Format: Book
• Published: Cambridge University Press, 2022-07-01T00:00:00Z.
• Subjects: article
• Online Access: Connect to this object online.

Background: Antibiotic resistance is pervasive in the Veterans' Affairs (VA) healthcare system, with rates of fluoroquinolone and trimethoprim-sulfamethoxazole (TMP/SMX) resistance approaching 30% in E. coli urinary isolates. The efficacy of antimicrobial treatment is critically dependent on th...