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Development of a knowledge-based simulator for haemodynamic support of septic shock

机译:基于知识的模拟器的开发,用于感染性休克的血流动力学支持

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The authors' previous work has demonstrated self-learning fuzzy control as a powerful, flexible and versatile control technique which adapts itself easily to changing patient conditions. It has never previously been applied to multiple input/output parameter controllers in medicine. The authors are investigating this technique for providing automated control of drug infusions supporting the cardiovascular and renal systems of patients in 'septic shock'. To construct the control system the authors are using this stratagem: modelling the shocked patient; verification of the model; validation of the model; controller strategy development in simulation using the validated model; physical control system development; clinical trials. Here, the authors highlight their validation techniques.
机译:作者的先前工作已经证明了自学习模糊控制是一种强大,灵活且用途广泛的控制技术,可以轻松地适应不断变化的患者状况。以前从未将它应用于医学中的多个输入/输出参数控制器。作者正在研究这种技术,以提供对“脓毒性休克”患者心血管和肾脏系统的药物输注的自动控制。为了构建控制系统,作者正在使用以下策略:对震惊的患者进行建模;模型验证;模型验证;使用已验证的模型在仿真中开发控制器策略;物理控制系统开发;临床试验。在这里,作者重点介绍了他们的验证技术。

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