Approximate-model closed-loop minimal sampling method for HIV viral-load minima detection.
Approximate-model closed-loop minimal sampling method for HIV viral-load minima detection.
复制标题
DOI：
10.1109/acc.2011.5991281
复制
发表时间：
2011
期刊：
影响因子：
--
通讯作者：
Rodriguez M
中科院分区：
文献类型：
--
作者：
Zurakowski R;Churgin M;Perez C;Rodriguez M
我们提出了一种闭环方法，用于确定正在经历治疗过渡的 HIV 患者的病毒反弹曲线的最小值。该方法使用模拟退火直接搜索算法来拟合病毒载量测量的简化近似解的参数。添加高斯白噪声，并获得拟合族。对拟合族应用安全容差测量以获得下一个采样时间。使用从 HIV 数据中识别的参数，我们表明该方法对从识别的患者模型生成的噪声数据表现出强大的性能，同时与固定间隔采样方法相比，大大减少了所需的样本数量。
We present a closed-loop method for determining the minimum of a viral rebound curve for an HIV patient undergoing a therapy transition. This method fits the parameters for a reduced approximate solution to the viral load measurements using a Simulated Annealing direct search algorithm. Gaussian white noise is added, and a family of fits is obtained. A safety tolerance measure is applied to the family of fits to obtain the next sample time. Using parameters identified from HIV data, we show that this method exhibits robust performance on noisy data generated from identified patient models, while greatly reducing the number of samples needed compared to a fixed-interval sampling approach.