Machine Learning Takes Laboratory Automation to the Next Level-Reference-Cited by-同舟云学术

Machine Learning Takes Laboratory Automation to the Next Level

Published:2020-03-25 Issue:4 Volume:58 Page:
ISSN:0095-1137
Container-title:Journal of Clinical Microbiology
language:en
Short-container-title:J Clin Microbiol

Author:

Ford Bradley A.¹,McElvania Erin²

Affiliation:

1. Department of Pathology, University of Iowa Hospitals and Clinics, Iowa City, Iowa, USA

2. Department of Pathology and Laboratory Medicine, NorthShore University HealthSystem, Evanston, Illinois, USA

Abstract

Clinical microbiology laboratories face challenges with workload and understaffing that other clinical laboratory sections have addressed with automation. In this issue of the Journal of Clinical Microbiology , 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.

Publisher

American Society for Microbiology

Subject

Microbiology (medical)

Link

https://journals.asm.org/doi/pdf/10.1128/JCM.00012-20

Reference16 articles.

1. The American Society for Clinical Pathology’s 2016-2017 Vacancy Survey of Medical Laboratories in the United States

2. Total Laboratory Automation in Clinical Microbiology: a Micro-Comic Strip

3. Automatic Digital Analysis of Chromogenic Media for Vancomycin-Resistant-Enterococcus Screens Using Copan WASPLab

4. Automated Scoring of Chromogenic Media for Detection of Methicillin-Resistant Staphylococcus aureus by Use of WASPLab Image Analysis Software

5. Evaluation of the WASPLab Segregation Software To Automatically Analyze Urine Cultures Using Routine Blood and MacConkey Agars

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