Molecular And Computational Modeling Of Cardiac Function
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Molecular and Computational Modeling of Cardiac Function
In Molecular and Computational Modeling of Cardiac Function, a group of prominent professors and researchers explain the fundamental concepts of molecular modeling and illustrate the biomedical applications. The book covers the following topics: Principles of atomistic modeling and simulation of biomolecular systems. Using atomistic modeling to predict the cardiotoxicity of an arrhythmia drug molecule. Bifurcation phenomena in cardiac system as control design of automaticity and arrhythmia. Modeling the role of myoglobin as a fatty acid transporter. Population-based computational approaches to investigate cardiac arrhythmia.
Artificial Intelligence for Computational Modeling of the Heart
Artificial Intelligence for Computational Modeling of the Heart presents recent research developments towards streamlined and automatic estimation of the digital twin of a patient's heart by combining computational modeling of heart physiology and artificial intelligence. The book first introduces the major aspects of multi-scale modeling of the heart, along with the compromises needed to achieve subject-specific simulations. Reader will then learn how AI technologies can unlock robust estimations of cardiac anatomy, obtain meta-models for real-time biophysical computations, and estimate model parameters from routine clinical data. Concepts are all illustrated through concrete clinical applications. - Presents recent advances in computational modeling of heart function and artificial intelligence technologies for subject-specific applications - Discusses AI-based technologies for robust anatomical modeling from medical images, data-driven reduction of multi-scale cardiac models, and estimations of physiological parameters from clinical data - Illustrates the technology through concrete clinical applications and discusses potential impacts and next steps needed for clinical translation
In Silico Clinical Trials for Cardiovascular Disease
This book covers in silico clinical trials of cardiovascular disease using a finite element and machine learning approach. Part I describes the fundamentals as well as the latest developments in the field: finite element modeling, system biology modeling for drug optimization, artificial intelligence approach for medical image processing, as well as pharmacokinetic and AI modeling. Part II provides use cases to describe how in silico clinical trials of cardiovascular disease are applied to specific cardiovascular diseases: carotid artery plaque modeling, aorta stenosis modeling, stent biodegradation modeling, surrogate AI model for left ventricle modeling, and more. This book is geared toward upper-level undergraduate and graduate students as well as for researchers in the domains of bioengineering, biomechanics, biomedical engineering and medicine.