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Commentary

Computer Vision and Artificial Intelligence Are Emerging Diagnostic Tools for the Clinical Microbiologist

Daniel D. Rhoads
Bobbi S. Pritt, Editor
Daniel D. Rhoads
aDepartment of Pathology, Case Western Reserve University, Cleveland, Ohio, USA
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Bobbi S. Pritt
Mayo Clinic
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DOI: 10.1128/JCM.00511-20
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ABSTRACT

Artificial intelligence (AI) is increasingly becoming an important component of clinical microbiology informatics. Researchers, microbiologists, laboratorians, and diagnosticians are interested in AI-based testing because these solutions have the potential to improve a test’s turnaround time, quality, and cost. A study by Mathison et al. used computer vision AI (B. A. Mathison, J. L. Kohan, J. F. Walker, R. B. Smith, et al., J Clin Microbiol 58:e02053-19, 2020, https://doi.org/10.1128/JCM.02053-19), but additional opportunities for AI applications exist within the clinical microbiology laboratory. Large data sets within clinical microbiology that are amenable to the development of AI diagnostics include genomic information from isolated bacteria, metagenomic microbial findings from primary specimens, mass spectra captured from cultured bacterial isolates, and large digital images, which is the medium that Mathison et al. chose to use. AI in general and computer vision in specific are emerging tools that clinical microbiologists need to study, develop, and implement in order to improve clinical microbiology.

The views expressed in this article do not necessarily reflect the views of the journal or of ASM.

FOOTNOTES

    • Accepted manuscript posted online 15 April 2020.
  • For the article discussed, see https://doi.org/10.1128/JCM.02053-19.

  • Copyright © 2020 American Society for Microbiology.

All Rights Reserved.

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Computer Vision and Artificial Intelligence Are Emerging Diagnostic Tools for the Clinical Microbiologist
Daniel D. Rhoads
Journal of Clinical Microbiology May 2020, 58 (6) e00511-20; DOI: 10.1128/JCM.00511-20

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Computer Vision and Artificial Intelligence Are Emerging Diagnostic Tools for the Clinical Microbiologist
Daniel D. Rhoads
Journal of Clinical Microbiology May 2020, 58 (6) e00511-20; DOI: 10.1128/JCM.00511-20
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KEYWORDS

artificial intelligence
bioinformatics
computer vision
digital pathology
microbiology
parasitology

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