"This book discusses how AI technologies can assist physicians to make better clinical decisions enabling early detection of subclinical organ dysfunction, through the use of clinically relevant information that can be found in the massive amount of data and, thus, improving quality and efficiency of healthcare delivery"--.

• Cover
• Title Page
• Copyright Page
• Book Series
• Table of Contents
• Detailed Table of Contents
• Preface
• Acknowledgment
• Introduction
• Chapter 1: SCA and SCD
• Chapter 2: A Review on IoT-Driven Technologies for Heart Disease Diagnosis and Prediction
• Chapter 3: Leveraging AI Technologies for Preventing and Detecting Sudden Cardiac Arrest and Death
• Chapter 4: Sudden Cardiac Arrest Detection by Feature Learning and Classification Using Deep Learning Architecture
• Chapter 5: Computer-Assistive Techniques for Monitoring and Tracking Patient Healthcare and Engagement
• Chapter 6: A Machine Learning Approach Towards Heart Attack Prediction
• Chapter 7: Assessment of Cardiac Dynamics and Risk Factor Analysis Using Deep Neural Nets
• Chapter 8: Designing Machine Learning-Based Variable-Order Bayesian Network in Predicting Sudden Cardiac Arrest and Death
• Chapter 9: Utilization of Artificial Intelligence-Based Wearable Sensors in Deep Residual Network for Detecting Heart Disease
• Chapter 10: PPG-Based Cardiovascular Disease Predictor Using Artificial Intelligence
• Compilation of References
• About the Contributors
• Index