Abstract
Our mostly manual, agar-based clinical microbiology laboratory is slowly but steadily being redefined by automation and innovation. Ironically, the oldest test, the Gram stain test, is still manually read and interpreted by trained personnel. In a proof-of-concept study, Smith et al. (J. Clin. Microbiol. 56:e01521-17, 2018, https://doi.org/10.1128/JCM.01521-17) used computer imaging with a deep convolutional neural network to examine and interpret Gram-stained slides from positive blood culture bottles. In light of the shortage of medical technologists/microbiologists and the need for results from positive blood culture bottles 24/7, this paper paves the way for the next innovations for the clinical microbiology laboratory of the future.