Accuracy of classification of urinary Gram-stain findings by a computer-aided diagnosis app compared with microbiology specialists.

ABSTRACT: Introduction. Timely and accurate diagnosis of bacterial infections enables early administration of appropriate antimicrobial treatment and improved outcomes.Hypothesis/Gap Statement. The accuracy of computer-aided diagnosis (CAD) for identifying organisms on urine Gram stains has not been compared with that of microbiology specialists (MS).Aim. To compare the interpretation of urine Gram-stain results by MS and a CAD app designed using artificial intelligence.Methodology. Urine specimens from patients with urinary tract infections were used and collected at two tertiary hospitals between 1 April and 31 December 2022. Using non-inferiority analysis to assess whether CAD was non-inferior to expert interpretation, CAD-predicted microscopic findings of the Gram-sta

SUBMITTER: Yamamoto K 

PROVIDER: S-EPMC12018707 | biostudies-literature | 2025 Apr

REPOSITORIES: biostudies-literature