Open AccessComputer Vision and Artificial Intelligence Are Emerging Diagnostic Tools for the Clinical Microbiologist
Author(s) -
Daniel D. Rhoads
Publication year - 2020
Publication title -
journal of clinical microbiology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.349
H-Index - 255
eISSN - 1070-633X
pISSN - 0095-1137
DOI - 10.1128/jcm.00511-20
Subject(s) - clinical microbiology , turnaround time , informatics , artificial intelligence , medical physics , computer science , medicine , data science , microbiology and biotechnology , biology , engineering , electrical engineering , operating system
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.