Leveraging AI for Predictive Modeling in Chronic Disease Management

Abstract

Artificial intelligence (AI) is revolutionizing chronic disease management by enabling predictive modeling that enhances early diagnosis, personalized treatment plans, and proactive healthcare interventions. Chronic diseases such as diabetes, cardiovascular disease, and chronic obstructive pulmonary disease (COPD) represent a significant global health burden, requiring continuous monitoring and tailored care. Leveraging AI for predictive modeling allows healthcare systems to anticipate disease progression, detect complications early, and optimize resource allocation. By utilizing machine learning (ML) and deep learning (DL) algorithms, AI can analyze large datasets, including electronic health records (EHRs), genetic data, and real-time information from wearable devices, to generate predictive insights. This paper explores the applications of AI in chronic disease management, focusing on how predictive modeling improves patient outcomes and reduces healthcare costs. It also discusses the challenges related to data privacy, algorithmic biases, and the integration of AI into traditional healthcare systems.