Direct antimicrobial resistance prediction from clinical MALDI-TOF mass spectra using machine learning

  14 January 2022

Early use of effective antimicrobial treatments is critical for the outcome of infections and the prevention of treatment resistance. Antimicrobial resistance testing enables the selection of optimal antibiotic treatments, but current culture-based techniques can take up to 72 hours to generate results. We have developed a novel machine learning approach to predict antimicrobial resistance directly from matrix-assisted laser desorption/ionization–time of flight (MALDI-TOF) mass spectra profiles of clinical isolates. 

Further reading: Nature Medicine
Author(s): Caroline Weis, Aline Cuénod, Bastian Rieck, Olivier Dubuis, Susanne Graf, Claudia Lang, Michael Oberle, Maximilian Brackmann, Kirstine K. Søgaard, Michael Osthoff, Karsten Borgwardt & Adrian Egli
Smart Innovations  


Unrestricted financial support by:

Antimicrobial Resistance Fighter Coalition


JSS University


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