A hierarchical Bayesian latent class mixture model with censorship for detection of linear temporal changes in antibiotic resistance.

A hierarchical Bayesian latent class mixture model with censorship for detection of linear temporal changes in antibiotic resistance.

Identifying and controlling the emergence of antimicrobial resistance (AMR) is a high priority for researchers and public health officials. One critical component of this control effort is timely detection of emerging or increasing resistance using surveillance programs. Currently, detection of temp...

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Bibliographic Details
Main Authors:	Min Zhang, Chong Wang, Annette O'Connor
Format:	Article
Language:	English
Published:	Public Library of Science (PLoS) 2020-01-01
Series:	PLoS ONE
Online Access:	https://doi.org/10.1371/journal.pone.0220427

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