Article

Using machine learning to predict antimicrobial minimum inhibitory concentrations and associated genomic features for nontyphoidal Salmonella

2018-07-31

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Nontyphoidal Salmonella species are the leading bacterial cause of food-borne disease in the United States. Whole genome sequences and paired antimicrobial susceptibility data are available for Salmonella strains because of surveillance efforts from public health agencies. In this study, a collection of 5,278 nontyphoidal Salmonella genomes, collected over 15 years in the United States, were used to generate XG...

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Literature Corpus work: 050f1032-184d-58e5-be6e-0ee834460b3d
DOI: 10.1101/380782

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Using machine learning to predict antimicrobial minimum inhibitory concentrations and associated genomic features for nontyphoidal <i>Salmonella</i>

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