Affiliation:
1. Universiti Brunei Darussalam, Brunei
2. VIT Bhopal University, India
Abstract
The rapid integration of artificial intelligence (AI) into the healthcare sector has opened up new opportunities for smart healthcare automation, transforming medical diagnosis, treatment, and overall patient care. However, the widespread adoption of AI algorithms in healthcare comes with challenges, particularly regarding transparency and explainability. This chapter explores the concept of explainable AI (XAI) and its crucial role in smart healthcare automation. The authors discuss the significance of XAI, various techniques for achieving explainability, and their potential applications in healthcare. Through case studies and success stories, the authors showcase real-world applications of XAI in radiology and chronic disease management. Lastly, they highlight future directions in XAI research for smart healthcare automation and emphasize the implications for healthcare providers and policymakers. By embracing XAI, the healthcare industry can unlock the full potential of AI while ensuring transparency, fairness, and improved patient outcomes.