This book explores the transformative potential of Explainable AI (XAI) in enhancing healthcare delivery and XAI's role in fostering transparency, trust, and accountability in AI-driven medical decision-making. Covering technical foundations, practical applications, and ethical considerations, it offers valuable insights into how XAI can improve clinical decision-making, patient outcomes, and healthcare operations. Through real-world case studies, the book illustrates the practical benefits of XAI in diverse healthcare scenarios. It also addresses the challenges and solutions related to deploying XAI, making it an essential resource for professionals and researchers. Detailed exploration of the methodologies, algorithms, and regulatory considerations underpinning XAI in smart healthcare systemsDiverse case studies demonstrating practical applications and benefits of XAI across various healthcare domains, enhancing understanding through tangible examplesExploration of innovative XAI applications in diagnosis, treatment, patient monitoring, and care delivery, showcasing its potential to revolutionize healthcare practices and improve outcomesDiscussion on how XAI promotes patient engagement by providing clear explanations of AI-driven diagnoses or treatment plans, enhancing patient understanding and participation in their healthcareBreakdown of XAI techniques, algorithms, and interpretability strategies, helping medical professionals understand and trust AI-driven decision-making processes