Machine Learning Takes Laboratory Automation to the Next Level
- PMID: 32024725
- PMCID: PMC7098768
- DOI: 10.1128/JCM.00012-20
Machine Learning Takes Laboratory Automation to the Next Level
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. 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.
Copyright © 2020 American Society for Microbiology.
Comment on
-
Evaluation of the WASPLab Segregation Software To Automatically Analyze Urine Cultures Using Routine Blood and MacConkey Agars.J Clin Microbiol. 2020 Mar 25;58(4):e01683-19. doi: 10.1128/JCM.01683-19. Print 2020 Mar 25. J Clin Microbiol. 2020. PMID: 31941690 Free PMC article.
References
-
- Faron ML, Buchan BW, Vismara C, Lacchini C, Bielli A, Gesu G, Liebregts T, van Bree A, Jansz A, Soucy G, Korver J, Ledeboer NA. 2016. Automated scoring of chromogenic media for detection of methicillin-resistant Staphylococcus aureus by use of WASPLab image analysis software. J Clin Microbiol 54:620–624. doi:10.1128/JCM.02778-15. - DOI - PMC - PubMed
Publication types
MeSH terms
LinkOut - more resources
Full Text Sources
Medical
