Artificial Intelligence (AI)-Powered Predictive Models in Chronic Disease Management: A Data-Driven Approach

Rajesh Munirathnam; Devidas Kanchetti

Authors

Rajesh Munirathnam Independent Researcher, Data Analytics with Artificial Intelligence, New Jersey, USA Author
Devidas Kanchetti Independent Researcher, Data Analytics with Artificial Intelligence, North Carolina, USA Author

Keywords:

Artificial Intelligence, Chronic Disease Management, Predictive Models, Neural Networks, Risk Stratification, Data Privacy, Personalized Medicine, Healthcare Technology, AI Ethics

Abstract

Artificial Intelligence (AI) has emerged as a transformative tool in chronic disease management, offering improved diagnostic accuracy, personalized treatment plans, and better patient outcomes. This paper explores the application of AI-powered predictive models in managing conditions such as diabetes and cardiovascular disease. Key findings demonstrate the effectiveness of AI in predicting disease progression, allowing for earlier interventions and risk stratification. Neural networks, random forests, and other machine learning models showed high accuracy, outperforming traditional management approaches. Despite these advancements, challenges such as data privacy, model interpretability, and generalizability persist. The paper highlights future directions for improving model transparency and addressing ethical concerns to broaden AI's impact in healthcare.

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