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0 (hodnocen0 x )

EB

ONLINE

Cham : Springer International Publishing AG, 2022

1 online resource (117 pages)

ISBN 9783031051647 (electronic bk.)

ISBN 9783031051630

Simula SpringerBriefs on Computing Ser. ; v.12

Print version: McCabe, Kimberly J. Computational Physiology Cham : Springer International Publishing AG,c2022 ISBN 9783031051630

Intro -- Preface -- Acknowledgements -- Contents -- Chapter 1 A Pipeline for Automated Coordinate Assignment in Anatomically Accurate Biventricular Models -- 1.1 Introduction -- 1.2 Methods -- 1.2.1 Semi-Automated Surface Extraction -- Algorithm 1 -- 1.2.2 Biventricular Coordinate System -- 1.2.2.1 Creation of the Coordinate System Cobiveco -- 1.2.3 Mapping Vector Fields -- 1.3 Results -- 1.4 Conclusion -- 1.4.1 Limitations -- References -- Chapter 2 3D Simulations of Fetal and Maternal Ventricular Excitation for Investigating the Abdominal ECG -- 2.1 Introduction -- 2.2 Methods -- 2.2.1 Geometrical mesh construction -- 2.2.2 Electrophysiological modelling -- 2.2.3 Extracellular potential measurements -- 2.2.4 Fetal ECG extraction using signal processing methods -- 2.3 Results -- 2.4 Discussion -- 2.5 Conclusions -- References -- Chapter 3 Ordinary Differential Equation-based Modeling of Cells in Human Cartilage -- 3.1 Introduction -- 3.2 Methods -- 3.2.1 Mathematical modelling of ATP-sensitive K+ currents -- 3.2.2 Population of Models -- 3.3 Results -- 3.3.1 Validation -- 3.3.2 Results for the ATP-sensitive K+ currents -- 3.3.3 Populations of Models -- 3.4 Discussion and Conclusion -- References -- Chapter 4 Conduction Velocity in Cardiac Tissue as Function of Ion Channel Conductance and Distribution -- 4.1 Introduction -- 4.2 Models and methods -- 4.2.1 The monodomain model -- 4.2.2 The EMI model -- 4.3 Results -- 4.4 Discussion -- 4.4.1 Influence of ion channel conductance on CV -- 4.4.2 Influence of ion channel distribution -- 4.5 Conclusions -- References -- Chapter 5 Computational Prediction of Cardiac Electropharmacology - How Much Does the Model Matter? -- 5.1 Introduction -- 5.2 Methods -- 5.2.1 Models of Cardiac Electrophysiology -- 5.2.2 Feature Extraction -- 5.2.3 Sensitivity Analysis and Translation -- 5.3 Results.

5.3.1 Model Translation -- 5.3.2 Translation Discrepancies -- 5.4 Discussion -- 5.5 Conclusion -- References -- Chapter 6 A Computational Study of Flow Instabilities in Aneurysms -- 6.1 Introduction -- 6.2 Methods -- 6.2.1 Baseflow equations -- 6.2.2 Flow perturbations and instability -- 6.2.3 Discretization -- 6.2.4 Computational Methodology -- 6.3 Results -- 6.4 Discussion -- References -- Chapter 7 Investigating the Multiscale Impact of Deoxyadenosine Triphosphate (dATP) on Pulmonary Arterial Hypertension (PAH) Induced Heart Failure -- 7.1 Introduction -- 7.2 Methods -- 7.2.1 Cell Level Changes -- 7.2.1.1 The SERCA Pump and Calcium transients -- 7.2.1.2 Cross-bridge cycling kinetics -- 7.2.2 Organ Level Model -- 7.3 Results -- 7.4 Discussion and Conclusion -- 7.5 Acknowledgements -- 7.6 Supplementary Information -- References -- Chapter 8 Identifying Ionic Channel Block in a Virtual Cardiomyocyte Population Using Machine Learning Classifiers -- 8.1 Introduction -- 8.2 Methods -- 8.2.1 Data -- 8.2.2 Preprocessing -- 8.2.2.1 Noise -- 8.2.2.2 Normalizing -- 8.2.2.3 Subtract drug signals from control signals -- 8.2.2.4 Vt and Ca2+ concatenation -- 8.2.3 Multi-label classification methods -- 8.2.3.1 Binary relevance -- 8.2.3.2 Classifier chains -- 8.2.3.3 Label Powerset -- 8.2.4 Model architectures -- 8.2.4.1 Gaussian Naive Bayes -- 8.2.4.2 Support Vector Classifier -- 8.2.4.3 XGBoost -- 8.2.4.4 Feed Forward Neural Network -- 8.2.4.5 Convolutional Neural Network -- 8.2.4.6 Recurrent Neural Network -- 8.2.5 Model selection and hyperparameter tuning -- 8.2.6 Scoring and metrics -- 8.2.6.1 Accuracy -- 8.2.6.2 Recall and precision -- 8.2.7 Explainable AI -- 8.2.7.1 LIME (Local Interpretable Model-Agnostic Explanations) -- 8.3 Results -- 8.4 Discussion -- 8.5 Conclusion -- References.

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