Clinical Diagnostic Biomarkers from the Personalization of Computational Models of Cardiac Physiology.

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Improved identifiability of myocardial material parameters by an energy-based cost function.Novel Computational Analysis of Left Atrial Anatomy Improves Prediction of Atrial Fibrillation Recurrence after Ablation.A Numerical Study of Scalable Cardiac Electro-Mechanical Solvers on HPC Architectures.

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P2860

Clinical Diagnostic Biomarkers from the Personalization of Computational Models of Cardiac Physiology.

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2015 nî lūn-bûn

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Clinical Diagnostic Biomarkers ...... Models of Cardiac Physiology.

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Clinical Diagnostic Biomarkers ...... Models of Cardiac Physiology.

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Clinical Diagnostic Biomarkers ...... Models of Cardiac Physiology.

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P1476

Clinical Diagnostic Biomarkers ...... Models of Cardiac Physiology.

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Nic Smith

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P2860

Computational medicine: translating models to clinical care

Integration from proteins to organs: the Physiome Project

Heart failure with normal left ventricular ejection fraction

Images as drivers of progress in cardiac computational modelling.

The Cardiac Atlas Project--an imaging database for computational modeling and statistical atlases of the heart

Aortic relative pressure components derived from four-dimensional flow cardiovascular magnetic resonance.

Understanding the need of ventricular pressure for the estimation of diastolic biomarkers.

Diastolic chamber properties of the left ventricle assessed by global fitting of pressure-volume data: improving the gold standard of diastolic function

Cardiac function estimation from MRI using a heart model and data assimilation: advances and difficulties.

Global identifiability of nonlinear models of biological systems.

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s10439-015-1439-8

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46-57

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scholarly article

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10.1007/S10439-015-1439-8

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Andrew N. Cookson

Pablo Lamata

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2015-09-23T00:00:00Z

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282153410

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biomarker

Clinical Diagnostic Biomarkers from the Personalization of Computational Models of Cardiac Physiology.

about

P2860

P2860

Clinical Diagnostic Biomarkers from the Personalization of Computational Models of Cardiac Physiology.

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