Department of Microbiology, Royal Hallamshire Hospital, Sheffield, United Kingdom.
Clin Microbiol Rev. 2011 Jul;24(3):515-56. doi: 10.1128/CMR.00061-10.
This review aims to discuss expert systems in general and how they may be used in medicine as a whole and clinical microbiology in particular (with the aid of interpretive reading). It considers rule-based systems, pattern-based systems, and data mining and introduces neural nets. A variety of noncommercial systems is described, and the central role played by the EUCAST is stressed. The need for expert rules in the environment of reset EUCAST breakpoints is also questioned. Commercial automated systems with on-board expert systems are considered, with emphasis being placed on the "big three": Vitek 2, BD Phoenix, and MicroScan. By necessity and in places, the review becomes a general review of automated system performances for the detection of specific resistance mechanisms rather than focusing solely on expert systems. Published performance evaluations of each system are drawn together and commented on critically.
这篇综述旨在讨论专家系统，以及它们如何在医学领域（借助解读）得到广泛应用，特别是在临床微生物学领域。文中介绍了基于规则的系统、基于模式的系统、数据挖掘和神经网络。描述了各种非商业系统，并强调了 EUCAST 在其中的核心作用。同时，文中还质疑了在 EUCAST 重置断点环境下是否需要专家规则。综述还考虑了带有内置专家系统的商业化自动系统，重点介绍了“三巨头”：Vitek 2、BD Phoenix 和 MicroScan。由于需要，文中有时会涉及自动系统性能的一般综述，而不仅仅是关注专家系统。综合了每个系统的已发表性能评估，并进行了批判性评论。
