Predicting Resistance in Pseudomonas aeruginosa With Machine Learning

  08 October 2019

When dealing with multidrug-resistant pathogens, every minute counts and any way to speed up the prediction of antimicrobial resistance (AMR) is key to reducing morbidity and mortality.

Infections with multidrug-resistant (MDR) Pseudomonas aeruginosa are increasing worldwide, and the organism is especially prevalent in health care-associated settings. But rapid AMR predictions could help with providing optimal care to patients.

Further reading: Contagion Live
Author(s): Alexandra Ward
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