Digital microbiology

Egli, Adrian; Schrenzel, Jacques; Greub, Gilbert Daniel

doi:10.1016/j.cmi.2020.06.023

Scientific article

Review

English

Digital microbiology

ContributorsEgli, Adrian; Schrenzel, Jacques; Greub, Gilbert Daniel

Published inClinical Microbiology and Infection, vol. 26, no. 10, p. 1324-1331

Publication date2020

Abstract

Digitalization and artificial intelligence have an important impact on the way microbiology laboratories will work in the near future. Opportunities and challenges lie ahead to digitalize the microbiological workflows. Making efficient use of big data, machine learning, and artificial intelligence in clinical microbiology requires a profound understanding of data handling aspects.

Keywords

Artificial Intelligence
Automation, Laboratory/methods
Big Data
Data Analysis
Diagnostic Tests, Routine/methods
Humans
Image Processing, Computer-Assisted/methods

Affiliation entities

Faculté de médecine / Section de médecine clinique / Département de médecine

Research groups

Génomique et microbiote (604)

Funding

Autre - Swiss Personalized Health Network driver project on Sepsis
Swiss National Science Foundation - Development of a Swiss surveillance database for molecular epidemiology of multi-drug resistant pathogens [177504]

Citation (ISO format)

EGLI, Adrian, SCHRENZEL, Jacques, GREUB, Gilbert Daniel. Digital microbiology. In: Clinical Microbiology and Infection, 2020, vol. 26, n° 10, p. 1324–1331. doi: 10.1016/j.cmi.2020.06.023

Article (Published version)

CC BY-NC-ND

Appendix

Identifiers

PID : unige:157589
DOI : 10.1016/j.cmi.2020.06.023
PMID : 32603804

Journal ISSN1198-743X

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Digital microbiology

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