Using Machine Learning To Predict Antimicrobial MICs and Associated Genomic Features for Nontyphoidal Salmonella-Reference-Cited by-同舟云学术

Using Machine Learning To Predict Antimicrobial MICs and Associated Genomic Features for Nontyphoidal Salmonella

Published:2019-02 Issue:2 Volume:57 Page:
ISSN:0095-1137
Container-title:Journal of Clinical Microbiology
language:en
Short-container-title:J Clin Microbiol

Author:

Nguyen Marcus¹²,Long S. Wesley³⁴^ORCID,McDermott Patrick F.⁵,Olsen Randall J.³⁴,Olson Robert¹²,Stevens Rick L.²⁶,Tyson Gregory H.⁵,Zhao Shaohua⁵,Davis James J.¹²

Affiliation:

1. University of Chicago Consortium for Advanced Science and Engineering, University of Chicago, Chicago, Illinois, USA

2. Computing, Environment and Life Sciences, Argonne National Laboratory, Argonne, Illinois, USA

3. Center for Molecular and Translational Human Infectious Diseases Research, Department of Pathology and Genomic Medicine, Houston Methodist Research Institute and Houston Methodist Hospital, Houston, Texas, USA

4. Department of Pathology and Laboratory Medicine, Weill Cornell Medical College, New York, New York, USA

5. U.S. Food and Drug Administration, Center for Veterinary Medicine, Office of Research, Laurel, Maryland, USA

6. Department of Computer Science, University of Chicago, Chicago, Illinois, USA

Abstract

Nontyphoidal Salmonella species are the leading bacterial cause of foodborne 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.

Funder

National Institute of Allergy and Infectious Diseases

Publisher

American Society for Microbiology

Subject

Microbiology (medical)

Link

https://journals.asm.org/doi/pdf/10.1128/JCM.01260-18

Reference71 articles.

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2. Preliminary incidence and trends of infection with pathogens transmitted commonly through food—Foodborne Diseases Active Surveillance Network, 10 US sites, 2006-2014;Crim SM;MMWR Morb Mortal Wkly Rep,2015

3. World Health Organization. 2015. WHO estimates of the global burden of foodborne diseases: foodborne disease burden epidemiology reference group 2007-2015. World Health Organization, Geneva, Switzerland.

4. Salmonella enterica: Survival, Colonization, and Virulence Differences among Serovars

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