Explainable Artificial Intelligence for Biomedical and Healthcare Applications (Explainable AI (XAI) for Engineering Applications)

✍ Scribed by Aditya Khamparia (editor), Deepak Gupta (editor)

• Publisher: CRC Press
• Year: 2024
• Tongue: English
• Leaves: 303
• Edition: 1
• Category: Library

✦ Synopsis

This reference text helps us understand how the concepts of explainable artificial intelligence (XAI) are used in the medical and healthcare sectors. The text discusses medical robotic systems using XAI and physical devices having autonomous behaviors for medical operations. It explores the usage of XAI for analyzing different types of unique data sets for medical image analysis, medical image registration, medical data synthesis, and information discovery. It covers important topics including XAI for biometric security, genomics, and medical disease diagnosis.

This book:

• Provides an excellent foundation for the core concepts and principles of explainable AI in biomedical and healthcare applications.

• Covers explainable AI for robotics and autonomous systems.

• Discusses usage of explainable AI in medical image analysis, medical image registration, and medical data synthesis.

• Examines biometrics security-assisted applications and their integration using explainable AI.

The text will be useful for graduate students, professionals, and academic researchers in diverse areas such as electrical engineering, electronics and communication engineering, biomedical engineering, and computer science.

✦ Table of Contents

Cover
Half Title
Series Page
Title Page
Copyright Page
Table of Contents
Preface
About the book
Editors
List of Contributors
Chapter 1 Exploring explainable AI: Techniques and comparative analysis
Chapter 2 Introduction to explainable artificial intelligence in biomedical and healthcare applications
Chapter 3 Smart healthcare system
Chapter 4 Explainable AI unlocks the potential of AI in biomedical research and practice
Chapter 5 An intuitive ensemble modelling with X-AI architecture for autism classification
Chapter 6 Mental disorder management using explainable artificial intelligence
Chapter 7 Unlocking insights
Chapter 8 Revolutionizing healthcare
Chapter 9 Mental disorders management using explainable artificial intelligence (XAI)
Chapter 10 Machine learning approach to predict adverse effects of mRNA vaccination
Chapter 11 Explainable artificial intelligence (EAI)
Chapter 12 Challenges and imperatives for equitable and ethical development of explainable AI in healthcare
Chapter 13 A comprehensive analysis of the convergence between deep learning technologies and bioinformatics, catalyzing groundbreaking innovations in biological data interpretation
Chapter 14 An exhaustive exploration of explainable AI-driven applications in healthcare, enhancing diagnostic accuracy, treatment efficacy, and patient trust
Chapter 15 An in-depth exploration of data analysis and processing through the prism of explainable artificial intelligence paradigms
Chapter 16 Implications of artificial intelligence in disease diagnosis
Index