

Quantitative estimates of the independent effect of the acquisition of ARGs on MIC add to the interpretability and utility of existing databases. Compared with approaches using machine learning models, the use of these estimates yields similar or better performance in the prediction of antibiotic resistance phenotype with more readily interpretable results. The methods outlined here could be readily applied to other antibiotic–pathogen combinations.
Microbe / Infectious Research
|15th Jan, 2026
|The Lancet
Microbe / Infectious Research
|15th Jan, 2026
|The Lancet
Microbe / Infectious Research
|15th Jan, 2026
|The Lancet
Microbe / Infectious Research
|15th Jan, 2026
|The Lancet
Microbe / Infectious Research
|15th Jan, 2026
|The Lancet
Microbe / Infectious Research
|15th Jan, 2026
|The Lancet
Microbe / Infectious Research
|15th Jan, 2026
|The Lancet