Full Description
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.
Contents
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
