Department of Pathology and Laboratory Medicine, VA Boston HealthCare System, West Roxbury, and Department of Pathology and Laboratory Medicine, Boston University School of Medicine, Boston, Massachusetts, USA
J Clin Microbiol. 2018 Feb 22;56(3). doi: 10.1128/JCM.01779-17. Print 2018 Mar.
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.
我们主要依靠人工和琼脂的临床微生物学实验室正在逐渐被自动化和创新所重新定义。具有讽刺意味的是，最古老的检测方法革兰氏染色试验仍然由经过培训的人员进行手动读取和解释。在一项概念验证研究中，Smith 等人（J. Clin. Microbiol. 56:e01521-17, 2018, https://doi.org/10.1128/JCM.01521-17）使用计算机成像和深度卷积神经网络来检查和解释阳性血培养瓶中的革兰氏染色载玻片。鉴于医学技术人员/微生物学家的短缺以及对 24/7 阳性血培养瓶结果的需求，本文为未来临床微生物学实验室的下一轮创新铺平了道路。
