论文标题
闭环糖尿病治疗的大规模虚拟临床试验中的高性能不确定性定量
High-performance Uncertainty Quantification in Large-scale Virtual Clinical Trials of Closed-loop Diabetes Treatment
论文作者
论文摘要
在本文中，我们提出了一项虚拟临床试验，用于评估闭环糖尿病治疗的性能和识别风险。虚拟临床试验可以对大量虚构患者（以数学模型表示）进行许多治疗变化的快速和无风险测试。我们使用在高性能软件和硬件中实现的闭环蒙特卡洛模拟，以量化治疗性能的不确定性以及在不同方案或不同闭环处理中比较性能。我们的软件可用于测试从启发式方法到非线性模型预测控制的各种控制策略。我们提供了一个虚拟临床试验的示例，在52周内对100万名患者进行了一项虚拟临床试验，我们使用高性能软件和硬件在1小时和22分钟内进行虚拟试验。
In this paper, we propose a virtual clinical trial for assessing the performance and identifying risks in closed-loop diabetes treatments. Virtual clinical trials enable fast and risk-free tests of many treatment variations for large populations of fictive patients (represented by mathematical models). We use closed-loop Monte Carlo simulation, implemented in high-performance software and hardware, to quantify the uncertainty in treatment performance as well as to compare the performance in different scenarios or of different closed-loop treatments. Our software can be used for testing a wide variety of control strategies ranging from heuristical approaches to nonlinear model predictive control. We present an example of a virtual clinical trial with one million patients over 52 weeks, and we use high-performance software and hardware to conduct the virtual trial in 1 h and 22 min.
