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Bayesian parameter inference and uncertainty-informed sensitivity analysis in a 0D cardiovascular model for intraoperative hypotension.

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第一作者： Jan-Niklas,Thiel

第一单位： Cardiovascular Engineering, Applied Medical Engineering, Medical Faculty, RWTH Aachen University, Aachen, Germany. Electronic address: thiel@ame.rwth-aachen.de.

作者： Jan-Niklas,Thiel ^[1] ; Marko,Zlicar ^[2] ; Ulrich,Steinseifer ^[3] ; Borut,Kirn ^[4] ; Michael,Neidlin ^[3]

作者单位： Cardiovascular Engineering, Applied Medical Engineering, Medical Faculty, RWTH Aachen University, Aachen, Germany. Electronic address: thiel@ame.rwth-aachen.de. ^[1] Clinical Department of Anaesthesiology and Intensive Therapy, University Medical Centre Ljubljana, Ljubljana, Slovenia. ^[2] Cardiovascular Engineering, Applied Medical Engineering, Medical Faculty, RWTH Aachen University, Aachen, Germany. ^[3] Institute of Physiology, Medical Faculty, University of Ljubljana, Ljubljana, Slovenia. ^[4]

关键词 Bayesian parameter inference Cardiovascular modeling Global sensitivity analysis Lumped parameter modeling Reduced-order modeling Uncertainty quantification

医学主题词人类(Humans);低血压(Hypotension);贝叶斯定理(Bayes Theorem);偏差(Uncertainty);模型, 心血管(Models, Cardiovascular);手术中并发症(Intraoperative Complications)

DOI 10.1016/j.compbiomed.2025.111371

PMID 41353885

发布时间 2025-12-21

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