Hunan University of Chinese Medicine, Changsha, 410208, People's Republic of China.
Hunan City University, Yiyang, 413000, People's Republic of China.
Sci Rep. 2023 Jul 19;13(1):11622. doi: 10.1038/s41598-023-38672-y.
Uncertainty in operating parameters during laser thermal pain treatment can yield unreliable results. To ensure reliability and effectiveness, we performed uncertainty analysis and optimization on these parameters. Firstly, we conducted univariate analysis to identify significant operational parameters. Next, an agent model using RBNN regression determined the relationship between these parameters, the constraint function, and the target function. Using interval uncertainty analysis, we obtained confidence distributions and established a nonlinear interval optimization model. Introducing RPDI transformed the model into a deterministic optimization approach. Solving this with a genetic algorithm yielded an optimal solution. The results demonstrate that this solution significantly enhances treatment efficacy while ensuring temperature control stability and reliability. Accounting for parameter uncertainties is crucial for achieving dependable and effective laser thermal pain treatment. These findings have important implications for advancing the clinical application of this treatment and enhancing patient outcomes.
激光热痛治疗过程中操作参数的不确定性可能导致不可靠的结果。为了确保可靠性和有效性，我们对这些参数进行了不确定性分析和优化。首先，我们进行了单变量分析以确定显著的操作参数。接下来，使用 RBNN 回归的代理模型确定了这些参数、约束函数和目标函数之间的关系。使用区间不确定性分析，我们获得了置信分布，并建立了一个非线性区间优化模型。引入 RPDI 将模型转换为确定性优化方法。使用遗传算法求解该模型得到了最优解。结果表明，该解决方案显著提高了治疗效果，同时确保了温度控制的稳定性和可靠性。考虑参数不确定性对于实现可靠有效的激光热痛治疗至关重要。这些发现对于推进该治疗的临床应用和改善患者预后具有重要意义。
