About the Book:
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.
Table of Contents
IntroductionMulti-scale Models of the Heart for Individualized SimulationsLearning Cardiac Anatomy: from Images to Heart AvatarData-Driven Reduction of Cardiac ModelsMachine Learning Methods for Robust Parameter Estimation Clinical ApplicationsConclusion and Perspective
