Abstract

Objective: Determination of preanesthetic high risk during surgical procedures using fuzzy risk evaluation. Material and Methods: In this study for the high risk patient classification, five major criteria comprising cardiac, pulmonary, renal or liver diseases and diabetes mellitus and three minor criteria comprising patients' age, body mass index and cigarette smoking were chosen to define the high-risk group. Since the fuzzy logic gives the ability to use linguistic expressions, that include the intuition of human operators or experts during the decision making process, it this study by using fuzzy logic modelling, rules for high risks were developed. To reach this aim a new fuzzy logic decision system is proposed that uses four input variables to calculate the risk as a percentage that is the output of the fuzzy system. Results: Using Fuzzy risk evaluation; By taking into account the number of inputs and number of their corresponding membership functions, it is deduced that 270 fuzzy rules will be enough. Conclusion: In this study, a risk classification model was developed by combining the risk criteria defined by previous medical studies and clinical experience with a fuzzy logic model in the preoperative period. This developed fuzzy logic model needs to be investigated by selecting specific groups of patients and specific operations.

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