AI-Enabled Data-Driven Approaches for Personalized Medicine and Healthcare Analytics
Dinesh Mendhe, Akriti Dogra, Prabha Shreeraj Nair, S. Punitha, K. S. Preetha, S. B. G. Tilak Babu
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.