Rosero-Garcia Esteban Emelio, Zurakowski Ryan
Assistant Professor of Electrical and Electronics Engineering at the Universidad del Valle, Cali Colombia
Proc Am Control Conf. 2010 Jul 29;2010:460-461. doi: 10.1109/acc.2010.5530993.
In previous work, we have developed optimal-control based approaches that seek to minimize the risk of subsequent virological failure by "pre-conditioning" the viral load during therapy switches. These techniques result in the transient susceptibility of the total viral load, and rely on finding the minimum of a dip in viral load and switching before viral load rebound. Model uncertainty necessitates a closed-loop approach to minimum-finding. Blood measurements are costly in terms of money, inconvenience and risk. In this paper, we introduce an iterative parameter estimation approach to find the viral load minimum, and measure the degree of optimality of minimum-seeking under conditions of measurement noise. We evaluate the cost-savings of this approach in terms of number of samples saved from a constant measurement rate.
在之前的工作中，我们开发了基于最优控制的方法，旨在通过在治疗转换期间对病毒载量进行“预处理”来将后续病毒学失败的风险降至最低。这些技术导致总病毒载量出现短暂的易感性，并依赖于找到病毒载量下降的最低点并在病毒载量反弹之前进行转换。模型的不确定性使得必须采用闭环方法来寻找最小值。血液检测在金钱、不便和风险方面成本高昂。在本文中，我们引入一种迭代参数估计方法来找到病毒载量的最小值，并在测量噪声条件下测量寻找最小值的最优程度。我们根据从恒定测量率中节省的样本数量来评估这种方法的成本节约情况。
