PREDICTIVE HEALTHCARE: LEVERAGING AI FOR EARLY DETECTION OF CHRONIC ILLNESSES

Abstract

The integration of Artificial Intelligence (AI) into healthcare has revolutionized the early detection and management of chronic illnesses. Predictive healthcare leverages machine learning algorithms, big data analytics, and clinical decision support systems to identify risk patterns, forecast disease progression, and personalize patient care. This study explores the transformative potential of AI-driven predictive models in diagnosing conditions such as diabetes, cardiovascular disease, and cancer at an early stage, thereby improving treatment outcomes and reducing healthcare costs. Emphasis is placed on the role of real-time health monitoring, electronic health records, and wearable devices in facilitating data collection and predictive accuracy. The paper also addresses challenges such as data privacy, algorithmic bias, and the need for ethical frameworks. By enhancing proactive interventions, AI offers a paradigm shift from reactive to preventive healthcare systems.