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 applicationsDiscusses 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 dataIllustrates the technology through concrete clinical applications and discusses potential impacts and next steps needed for clinical translation

1. Introduction 2. Multi-scale Models of the Heart for Individualized Simulations 3. Learning Cardiac Anatomy: from Images to Heart Avatar 4. Data-Driven Reduction of Cardiac Models 5. Machine Learning Methods for Robust Parameter Estimation 6. Clinical Applications 7. Conclusion and Perspective