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
Smart Innovations  


Unrestricted financial support by:

Antimicrobial Resistance Fighter Coalition


JSS University

Technology Database

Display your AMR Technology, Product and Service

Suppliers and Users of Technologies, Products and Services benefit from CAPI.
CAPI (Continuous AMR Partnering Initiative) unites Suppliers and Users worldwide with the aim to add to the curbing of AMR.

Read more and make your own Technology Page >>
What is going on with AMR?
Stay tuned with remarkable global AMR news and developments!