Machine learning for microbial identification and antimicrobial susceptibility testing on MALDI-TOF mass spectra: a systematic review.

Journal: Clinical microbiology and infection : the official publication of the European Society of Clinical Microbiology and Infectious Diseases
Published Date: Mar 23, 2020

Abstract

BACKGROUND: The matrix assisted laser desorption/ionization and time-of-flight mass spectrometry (MALDI-TOF MS) technology has revolutionized the field of microbiology by facilitating precise and rapid species identification. Recently, machine learning techniques have been leveraged to maximally exploit the information contained in MALDI-TOF MS, with the ultimate goal to refine species identification and streamline antimicrobial resistance determination.

Authors

  • C V Weis
    Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland; SIB Swiss Institute of Bioinformatics, Switzerland. Electronic address: caroline.weis@bsse.ethz.ch.
  • C R Jutzeler
    Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland; SIB Swiss Institute of Bioinformatics, Switzerland.
  • K Borgwardt
    Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland; SIB Swiss Institute of Bioinformatics, Switzerland.

Keywords

External Resources

Popular Topics
Recent Journals