title: Expert systems in clinical microbiology.
abstract: 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.
authors: Department of Microbiology, Royal Hallamshire Hospital, Sheffield, United Kingdom. tgwinstanley@hotmail.com
authors: Trevor
authors: T
authors: Winstanley
authors: Patrice
authors: P
authors: Courvalin
mesh_terms: D000900:Anti-Bacterial Agents / Q000494:pharmacology*; D001331:Automation; D005103:Expert Systems; D006090:Gram-Negative Bacteria / Q000187:drug effects; D006095:Gram-Positive Cocci / Q000187:drug effects; D006801:Humans; D008826:Microbial Sensitivity Tests / Q000379:methods*
chemical_list: D000900:Anti-Bacterial Agents