Calibrating cardiac electrophysiology models using latent Gaussian processes on atrial manifolds.
Calibrating cardiac electrophysiology models using latent Gaussian processes on atrial manifolds.
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DOI:
10.1038/s41598-022-20745-z
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发表时间:
2022-10-04
影响因子:
4.6
通讯作者:
Clayton, Richard H.
中科院分区:
文献类型:
--
作者:
Coveney, Sam;Roney, Caroline H.;Corrado, Cesare;Wilkinson, Richard D.;Oakley, Jeremy E.;Niederer, Steven A.;Clayton, Richard H.
Models of electrical excitation and recovery in the heart have become increasingly detailed, but have yet to be used routinely in the clinical setting to guide personalized intervention in patients. One of the main challenges is calibrating models from the limited measurements that can be made in a patient during a standard clinical procedure. In this work, we propose a novel framework for the probabilistic calibration of electrophysiology parameters on the left atrium of the heart using local measurements of cardiac excitability. Parameter fields are represented as Gaussian processes on manifolds and are linked to measurements via surrogate functions that map from local parameter values to measurements. The posterior distribution of parameter fields is then obtained. We show that our method can recover parameter fields used to generate localised synthetic measurements of effective refractory period. Our methodology is applicable to other measurement types collected with clinical protocols, and more generally for calibration where model parameters vary over a manifold.
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影响因子:
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作者:
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通讯作者:
Niederer SA
影响因子:
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作者:
Coveney S;Corrado C;Oakley JE;Wilkinson RD;Niederer SA;Clayton RH
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PERTSOV, AM
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