This book explores the intersection of artificial intelligence (AI) and healthcare data analytics. This comprehensive edited volume explores the application of AI-driven techniques, including machine learning, deep learning, and data mining, in addressing complex challenges in healthcare management. Through a combination of theoretical discussions, practical applications, and real-world case studies, this book provides insights into the latest innovations shaping the future of healthcare delivery and patient care.
This publication will have a transformative impact on the research community by advancing the understanding of how AI-driven innovations can revolutionize healthcare data analytics and management. By showcasing state-of-the-art strategies, applications, and case studies, the book will inspire researchers to explore new avenues for research and innovation in AI-driven healthcare analytics. Furthermore, it will contribute to interdisciplinary collaboration by bridging the gap between healthcare management, data science, and engineering disciplines, fostering a more holistic approach to addressing healthcare challenges.
This book is intended for researchers, practitioners, and students across a broad spectrum of disciplines, including industrial engineering, computer science, healthcare management, and data science. It will serve as a valuable resource for academics seeking to deepen their knowledge of AI-driven approaches in healthcare data analytics and management. Practitioners working in healthcare organizations will find practical insights and case studies that can inform decision-making processes and drive organizational improvements. Additionally, graduate students and professionals aiming to explore the latest advancements in AI-driven healthcare analytics will benefit from the diverse perspectives presented in this book.