Artificial Intelligence in Antibiotic Selection

Hatice SINAV ÜTKÜa

aKocaeli University Faculty of Medicine, Division of Pediatric Infectious Diseases, Kocaeli, Türkiye

ABSTRACT

Antibiotics, since their discovery in 1928, have revolutionized healthcare, but their misuse has given rise to antibiotic resistance, which threatens global health, causing 700,000 annual deaths, with estimates of 10 million by 2050. This issue demands urgent solutions.
Artificial intelligence has emerged as a critical player in the battle against antibiotic resistance. Artificial intelligence assists physicians in antibiotic selection, improves diagnostic accuracy, and aids in developing novel antimicrobials. Machine learning models predict antibiotic resistance events and alert healthcare providers.
Three main artificial intelligence application categories for antibiotic resistance exist:

  1. Prediction of antibiotic resistance: Artificial intelligence accelerates antimicrobial susceptibility testing, providing faster and reliable results. Whole-genome sequencing-based antimicrobial susceptibility testing enhances accuracy with large datasets.
  2. Facilitating appropriate antibiotic use: Artificial intelligence-driven clinical support systems aid antibiotic selection. Natural Language Processing improves electronic health record collection.
  3. Developing new antimicrobials: Artificial intelligence contributes to developing antimicrobial peptides and synergistic drug combinations as alternatives to traditional antibiotics.
    Despite challenges like data sharing and clinician training, artificial intelligence offers hope in the fight against antibiotic resistance. Integrating artificial intelligence with medical expertise promises substantial improvements in antimicrobial management, crucial for global health security.

Keywords: Artificial intelligence; antibiotic stewardship; pediatrics

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