Machine Learning Takes Laboratory Automation to the Next Level

Bradley A Ford; Erin McElvania

doi:10.1128/JCM.00012-20

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Machine Learning Takes Laboratory Automation to the Next Level

Journal article

Open access

Peer reviewed

Machine Learning Takes Laboratory Automation to the Next Level

Bradley A Ford and Erin McElvania

Journal of clinical microbiology, Vol.58(4), e00012-20

03/25/2020

DOI: 10.1128/JCM.00012-20

PMID: 32024725

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Abstract

Clinical microbiology laboratories face challenges with workload and understaffing that other clinical laboratory sections have addressed with automation. In this issue of the , M. L. Faron, B. W. Buchan, R. F. Relich, J. Clark, and N. A. Ledeboer (J Clin Microbiol 58:e01683-19, 2020, https://doi.org/10.1128/JCM.01683-19) evaluate the performance of automated image analysis software to screen urine cultures for further workup according to their total number of CFU. Urine cultures are the highest volume specimen type for most laboratories, so this software has the potential for tremendous gains in laboratory efficiency and quality due to the consistency of colony quantification.

Details

Title: Subtitle: Machine Learning Takes Laboratory Automation to the Next Level
Creators: Bradley A Ford - University of Iowa Hospitals and Clinics
Erin McElvania - NorthShore University HealthSystem
Resource Type: Journal article
Publication Details: Journal of clinical microbiology, Vol.58(4), e00012-20
DOI: 10.1128/JCM.00012-20
PMID: 32024725
NLM abbreviation: J Clin Microbiol
ISSN: 0095-1137
eISSN: 1098-660X
Language: English
Date published: 03/25/2020
Academic Unit: Pathology
Record Identifier: 9984186390302771

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