Machine learning and matrix-assisted laser desorption/ionization time-of-flight mass spectra for antimicrobial resistance prediction: A systematic review of recent advancements and future development.

Journal: Journal of chromatography. A
Published Date:

Abstract

BACKGROUND: The use of matrix-assisted laser desorption/ionization time-of-flight mass spectra (MALDI-TOF MS) combined with machine learning techniques has recently emerged as a method to address the public health crisis of antimicrobial resistance. This systematic review, conducted following Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guidelines, aims to evaluate the current state of the art in using machine learning for the detection and classification of antimicrobial resistance from MALDI-TOF mass spectrometry data.

Authors

  • Xaviera A López-Cortés
    Department of Computer Sciences and Industries, Universidad Católica del Maule, Talca, 3480112, Chile; Centro de Innovación en Ingeniería Aplicada (CIIA), Universidad Católica del Maule, Talca, 3480112, Chile. Electronic address: xlopez@ucm.cl.
  • José M Manríquez-Troncoso
    Department of Computer Sciences and Industries, Universidad Católica del Maule, Talca, 3480112, Chile.
  • John Kandalaft-Letelier
    Department of Computer Sciences and Industries, Universidad Católica del Maule, Talca, 3480112, Chile.
  • Sara Cuadros-Orellana
    Centro de Biotecnología de los Recursos Naturales, Universidad Católica del Maule, Talca, 3480112, Chile.