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Computer Vision and Artificial Intelligence Are Emerging Diagnostic Tools for the Clinical Microbiologist.
Rhoads, Daniel D.
Affiliation
  • Rhoads DD; Department of Pathology, Case Western Reserve University, Cleveland, Ohio, USA daniel.rhoads@case.edu.
J Clin Microbiol ; 58(6)2020 05 26.
Article in En | MEDLINE | ID: mdl-32295889
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 58e02053-19, 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.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Artificial Intelligence / Clinical Laboratory Services Type of study: Diagnostic_studies / Prognostic_studies Language: En Journal: J Clin Microbiol Year: 2020 Type: Article Affiliation country: United States

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Artificial Intelligence / Clinical Laboratory Services Type of study: Diagnostic_studies / Prognostic_studies Language: En Journal: J Clin Microbiol Year: 2020 Type: Article Affiliation country: United States