Cardozo E Fabian, Zurakowski Ryan
Electrical and Computer Engineering, University of Delaware, Newark, DE 19716, USA.
Annu Int Conf IEEE Eng Med Biol Soc. 2011;2011:116-9. doi: 10.1109/IEMBS.2011.6089910.
We test the robustness of a closed-loop treatment scheduling method to realistic HIV viral load measurement error. The purpose of the algorithm is to allow the accurate detection of an induced viral load minimum with a reduced number of samples. Therapy must be switched at or near the viral-load minimum to achieve optimal therapeutic benefit; therapeutic benefit decreases logarithmically with increased viral load at the switching time. The performance of the algorithm is characterized using a number of metrics. These include the number of samples saved vs. fixed-rate sampling, the risk-reduction achieved vs. the risk-reduction possible with frequent sampling, and the difference between the switching time vs. the theoretical optimal switching time. The algorithm is applied to simulated patient data generated from a family of data-driven patient models and corrupted by experimentally confirmed levels of log-normal noise.
我们测试了一种闭环治疗调度方法对于实际HIV病毒载量测量误差的稳健性。该算法的目的是通过减少样本数量来准确检测诱导的病毒载量最小值。治疗必须在病毒载量最小值处或其附近切换，以实现最佳治疗效果；治疗效果会随着切换时病毒载量的增加而呈对数下降。该算法的性能通过多种指标来表征。这些指标包括与固定速率采样相比节省的样本数量、与频繁采样可能实现的风险降低相比所实现的风险降低，以及切换时间与理论最优切换时间之间的差异。该算法应用于从一系列数据驱动的患者模型生成并被实验确定的对数正态噪声水平所破坏的模拟患者数据。
