Article

Predicting S. aureus antimicrobial resistance with interpretable genomic space maps

2023-02-24

Abstract excerpt

Increasing antimicrobial resistance (AMR) represents a global healthcare threat. Methods for rapid selection of optimal antibiotic treatment are urgently needed to decrease the spread of AMR and associated mortality. The use of machine learning (ML) techniques based on genomic data to predict resistance phenotypes serves as a solution for the acceleration of the clinical response prior to phenotypic testing. Nonet...

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Literature Corpus work: 726d0e2b-8261-501b-9f3c-cbda4619764b
DOI: 10.1101/2023.02.24.529878

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