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A Neuro-Fuzzy approach for predicting hemodynamic responses during anesthesia

机译:一种用于预测麻醉期间血流动力学反应的神经模糊方法

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The effect of drugs' interaction on the hemodynamic variables is of great importance when considering patient's safety and stability. It is also important for control infusion systems during anesthesia. In this article, an adaptive-network fuzzy inference system is used to model the effect of two drugs (propofol and remifentanil) on the mean arterial pressure and heart rate. The clinical data of 45 patients is used to train and test the model. The use of subtractive clustering improved the model performance on the testing data set. The fuzzy model is able to capture the synergistic interaction between the two drugs, but other influences were detected.
机译:当考虑患者的安全性和稳定性时,药物对血流动力学变量对血流动力变量的影响非常重要。在麻醉期间控制输注系统也很重要。在本文中,自适应网络模糊推理系统用于模拟两种药物(Favofol和Remifentanil)对平均动脉压和心率的影响。 45名患者的临床资料用于培训和测试模型。减法聚类的使用改进了测试数据集的模型性能。模糊模型能够捕获两种药物之间的协同相互作用,但检测到其他影响。

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