Machine Learning for Antimicrobial Resistance Prediction: Current Practice, Limitations, and Clinical Perspective-Reference-Cited by-同舟云学术

Machine Learning for Antimicrobial Resistance Prediction: Current Practice, Limitations, and Clinical Perspective

Published:2022-09-21 Issue:3 Volume:35 Page:
ISSN:0893-8512
Container-title:Clinical Microbiology Reviews
language:en
Short-container-title:Clin Microbiol Rev

Author:

Kim Jee In¹²³^ORCID,Maguire Finlay¹²⁴⁵⁶^ORCID,Tsang Kara K.⁷^ORCID,Gouliouris Theodore⁸⁹¹⁰,Peacock Sharon J.⁸,McAllister Tim A.³^ORCID,McArthur Andrew G.¹¹¹²¹³^ORCID,Beiko Robert G.¹²^ORCID

Affiliation:

1. Faculty of Computer Science, Dalhousie University, Halifax, Canada

2. Institute for Comparative Genomics, Dalhousie University, Halifax, Canada

3. Lethbridge Research and Development Centre, Agriculture and Agri-Food Canada, Lethbridge, Canada

4. Department of Community Health and Epidemiology, Faculty of Medicine, Dalhousie University, Halifax, Canada

5. Shared Hospital Laboratory, Toronto, Canada

6. Sunnybrook Research Institute, Sunnybrook Health Sciences Centre, Toronto, Canada

7. London School of Hygiene & Tropical Medicine, London, United Kingdom

8. Department of Medicine, University of Cambridge, Cambridge, United Kingdom

9. Clinical Microbiology and Public Health Laboratory, Public Health England, Cambridge, United Kingdom

10. Cambridge University Hospitals NHS Foundation Trust, Cambridge, United Kingdom

11. David Braley Centre for Antibiotic Discovery, McMaster University, Hamilton, Canada

12. M.G. DeGroote Institute for Infectious Disease Research, McMaster University, Hamilton, Canada

13. Department of Biochemistry and Biomedical Sciences, McMaster University, Hamilton, Canada

Abstract

Antimicrobial resistance (AMR) is a global health crisis that poses a great threat to modern medicine. Effective prevention strategies are urgently required to slow the emergence and further dissemination of AMR.

Funder

Gouvernement du Canada | Agriculture and Agri-Food Canada

Publisher

American Society for Microbiology

Subject

Infectious Diseases,Microbiology (medical),Public Health, Environmental and Occupational Health,General Immunology and Microbiology,Epidemiology

Link

https://journals.asm.org/doi/pdf/10.1128/cmr.00179-21

Reference136 articles.

1. Global burden of bacterial antimicrobial resistance in 2019: a systematic analysis

2. Enumerating the economic cost of antimicrobial resistance per antibiotic consumed to inform the evaluation of interventions affecting their use

3. Federal Government of Canada. 2014. Antimicrobial resistance and use in Canada: a federal framework for action. Federal Government of Canada Ottawa Canada.

4. World Health Organization. 2015. Global action plan on antimicrobial resistance. World Health Organization Geneva Switzerland.

5. UK Review on AMR. 2016. Tackling drug-resistant infections globally: final report and recommendations. https://amr-review.org/home.html.

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