Gaussian process regressions for inverse problems and parameter searches in models of ventricular mechanics › Research Explorer

Gaussian process regressions for inverse problems and parameter searches in models of ventricular mechanics

Research output: Contribution to journal › Article › peer-review

DOI

https://doi.org/10.3389/fphys.2018.01002
Final published version

Paolo Di Achille
Ahmed Harouni
Svyatoslav Khamzin
Olga Solovyova
John J. Rice
Viatcheslav Gurev

Original language	English
Article number	1002
Number of pages	17
Journal	Frontiers in Physiology
Volume	9
Issue number	AUG
DOIs	https://doi.org/10.3389/fphys.2018.01002
Publication status	Published - 14 Aug 2018

Research areas

FEM, Infarct model, Inverse optimization, Kriging, LV mechanics, Statistical learning, Unloaded configuration, statistical learning, inverse optimization, kriging, QUANTIFICATION, PASSIVE MYOCARDIUM, HEART, COMPUTER, DEFORMATIONS, FRAMEWORK, DYNAMICS, infarct model, unloaded configuration, OPTIMIZATION, PROPAGATION, GEOMETRY

WoS ResearchAreas Categories

Physiology

ASJC Scopus subject areas

Physiology (medical)
Physiology

ID: 7764231