The X-Factor of Healthcare
Shahin Shoukat Makubhai, Ganesh Rajaram Pathak, Pankaj R. Chandre · Advances in healthcare information systems and administration book series · 2024
This chapter explores the revolutionary impact of explainable AI in transforming medical practices. The X-Factor of Healthcare highlights how the integration of explainable AI technologies enables healthcare professionals to gain valuable insights into complex decision-making processes. By providing interpretable and transparent explanations for AI-driven predictions and recommendations, explainable AI empowers medical practitioners to understand, trust, and utilize AI tools more effectively. This Chapter examines the key benefits and challenges of implementing explainable AI in healthcare settings, emphasizing the improvement in diagnostic accuracy, personalized treatment plans, and patient outcomes. Additionally, this chapter discusses the results of machine learning classifiers such as Support Vector Machine, Random Forest, Decision Tree, and Logistic regression. This chapter also discusses the importance of ethical considerations, regulatory guidelines, and the need for collaboration between AI experts and healthcare professionals.