AI-Enabled Data-Driven Approaches for Personalized Medicine and Healthcare Analytics

Abstract

In the context of personalized medicine and healthcare analytics, this study digs into the potentially game-changing area of AI-enabled data-driven Approaches. Our research demonstrates the possibility of using a deep neural network for illness outcome prediction, with interpretability ensured by SHAP values. Both the importance of AI in facilitating personalized therapy, data-driven insights, and ethical compliance and the need for robust model performance are emphasized in the study. The study's results provide an appealing picture of a future in which healthcare is more accurate, efficient, and patient-centered as the healthcare environment continues to change. This study sets the groundwork for an AI-driven healthcare ecosystem where innovations improve the quality and delivery of care, as well as patient outcomes, treatment, and medical research.