Synthesis of an anaesthetic agent administration system using fuzzy inductive reasoning.
Control of the depth of anaesthesia is a difficult undertaking. Progress has been made during recent years by use of different methodologies and monitoring systems that suggest the safe amount of an anaesthetic drug, considering the condition of an individual patient. Despite these improvements, anaesthetists still rely heavily on personal experience when suggesting the anaesthetic dosage during surgical operations. The purposes of this paper are twofold. One is a description of the design of an anaesthetic agent control system using a qualitative modelling and simulation methodology called Fuzzy Inductive Reasoning (FIR). A comparison with a system developed for the same application using a neural network approach is also presented. The second purpose is a discussion of the problem of separating system-generic from patient-specific behaviour in the context of inductive modeling using the FIR methodology. In order to be useful, the model generated by FIR should reflect upon system-generic behavioural characteristics exclusively, while suppressing patient-specific behavioural patterns. A technique based on combining knowledge obtained from different patients is designed that makes it possible to derive a single model characterizing a specific class of similar patients undergoing similar operations, preserving the common characteristics of all these patients while filtering out the specific behavioural patterns of any one of the individual patients from whom the data were obtained.
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Llenguatges i Sistemes Informàtics, Universitat Politècnica de Catalunya, Barcelona, Spain.
Cellier
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D000777:Anesthetics / Q000008:administration & dosage*; D001185:Artificial Intelligence; D003198:Computer Simulation; D016503:Drug Delivery Systems; D017143:Fuzzy Logic; D006801:Humans; D008962:Models, Theoretical; D016571:Neural Networks, Computer
D000777:Anesthetics