降低人类心房细胞建模时的复杂性和不可识别性
Reducing complexity and unidentifiability when modelling human atrial cells
摘要：
心脏建模中细胞动作电位的数学模型已经变得越来越复杂，特别是在控制单个离子通道电流的打开和关闭的门控动力学中。随着心脏模型在个性化医疗中的应用，为临床决策提供信息，了解从校准到实验数据的参数估计中隐藏的不确定性至关重要。本研究应用近似贝叶斯计算将两个现有人类心房细胞模型中的四个离子通道的门控动力学重新校准到其原始数据集，提供了一种不确定性的度量，并指示了在给定可用实验数据的情况下选择单个唯一值的潜在问题。研究了两种方法来减少存在的不确定性：重新校准模型以获得更完整的数据集，并使用具有较少参数的较不复杂的配方来约束。将重新校准的模型插入到全细胞模型中，以研究对动作电位的总体影响。使用更完整的数据集并不能消除参数估计中存在的不确定性。不太复杂的模型，特别是对于快速钠电流，给出了更好的拟合实验数据，同时降低了参数不确定性和提高了计算速度。
英文摘要：
Mathematical models of a cellular action potential in cardiac modelling have become increasingly complex, particularly in gating kinetics which control the opening and closing of individual ion channel currents. As cardiac models advance towards use in personalised medicine to inform clinical decision-making, it is critical to understand the uncertainty hidden in parameter estimates from their calibration to experimental data. This study applies approximate Bayesian computation to re-calibrate the gating kinetics of four ion channels in two existing human atrial cell models to their original datasets, providing a measure of uncertainty and indication of potential issues with selecting a single unique value given the available experimental data. Two approaches are investigated to reduce the uncertainty present: re-calibrating the models to a more complete dataset and using a less complex formulation with fewer parameters to constrain. The re-calibrated models are inserted back into the full cell model to study the overall effect on the action potential. The use of more complete datasets does not eliminate uncertainty present in parameter estimates. The less complex model, particularly for the fast sodium current, gave a better fit to experimental data alongside lower parameter uncertainty and improved computational speed.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
