敏感性分析和模型评估:动脉血流和血压的数学模型。

Laura M Ellwein, Hien T Tran, Cheryl Zapata, Vera Novak, Mette S Olufsen
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引用次数: 88

摘要

近年来,为了更准确地解释生理动力学,描述心血管系统的数学模型变得越来越复杂。为了帮助模型验证和设计,对Olufsen, Tran, Ottesen, Ellwein, Lipsitz和Novak首先提出的心血管模型进行了经典的确定性敏感性分析(应用物理学报99(4):1523- 1537,2005)。该模型使用11个微分状态方程和52个参数来预测动脉血流和血压。计算了模型状态方程对各参数的相对灵敏度解,并对各参数进行了灵敏度排序。参数分为敏感参数和不敏感参数两组。敏感参数的微小变化对模型解的影响很大,而不敏感参数的变化对模型解的影响可以忽略不计。该方法使有效参数空间缩短了一半以上,计算时间缩短了三分之二。此外,设计了一个更简单的模型,保留了原模型的必要特征,但具有三分之二的状态方程和一半的模型参数。
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Sensitivity analysis and model assessment: mathematical models for arterial blood flow and blood pressure.

The complexity of mathematical models describing the cardiovascular system has grown in recent years to more accurately account for physiological dynamics. To aid in model validation and design, classical deterministic sensitivity analysis is performed on the cardiovascular model first presented by Olufsen, Tran, Ottesen, Ellwein, Lipsitz and Novak (J Appl Physiol 99(4):1523-1537, 2005). This model uses 11 differential state equations with 52 parameters to predict arterial blood flow and blood pressure. The relative sensitivity solutions of the model state equations with respect to each of the parameters is calculated and a sensitivity ranking is created for each parameter. Parameters are separated into two groups: sensitive and insensitive parameters. Small changes in sensitive parameters have a large effect on the model solution while changes in insensitive parameters have a negligible effect. This analysis was successfully used to reduce the effective parameter space by more than half and the computation time by two thirds. Additionally, a simpler model was designed that retained the necessary features of the original model but with two-thirds of the state equations and half of the model parameters.

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