"This book focuses on the Explainable Artificial Intelligence (XAI) for healthcare, providing a broad overview of state-of-art approaches for accurate analysis and diagnosis, and encompassing computational vision processing techniques that handle complex data like physiological information, electronic healthcare records, medical imaging data that assist in earlier prediction"--.

• Cover
• Title Page
• Copyright Page
• Book Series
• Table of Contents
• Detailed Table of Contents
• Foreword
• Preface
• Acknowledgment
• Chapter 1: Deep Learning Model for Diagnosing Diabetes
• Chapter 2: Analysis of Cardiovascular Disease Prediction Using Model-Agnostic Explainable Artificial Intelligence Techniques
• Chapter 3: Role of Deep Learning in Medical Image Super-Resolution
• Chapter 4: Analyzing and Forecasting of COVID-19 Situation Using FbProphet Model Algorithms
• Chapter 5: Role of Explainable Artificial Intelligence (XAI) in Prediction of Non-Communicable Diseases (NCDs)
• Chapter 6: Drug Discovery With XAI Using Deep Learning
• Chapter 7: Development of Machine Learning Models for Healthcare Systems Using Python
• Chapter 8: Topical Repute on Artificial Intelligence-Based Approaches in COVID-19 Supervision
• Chapter 9: An Efficient Multi-Layer Perceptron Neural Network-Based Breast Cancer Prediction
• Chapter 10: A Model-Based Approach for Extracting Emotional Status From Immobilized Beings Using EEG Signals
• Chapter 11: Basic Issues and Challenges on Explainable Artificial Intelligence (XAI) in Healthcare Systems
• Chapter 12: Principles and Methods of Explainable Artificial Intelligence in Healthcare
• Compilation of References
• About the Contributors
• Index