Predictive Analytics for Early Detection of Chronic Diseases Using Machine Learning
Abstract
This study explores the application of machine learning algorithms in predicting chronic diseases such as diabetes and hypertension. By analyzing patient data from electronic health records, we developed a predictive model that identifies at-risk individuals with high accuracy. Our findings demonstrate the potential of AI-driven analytics to enhance early detection and improve patient outcomes, ultimately leading to more effective interventions and resource allocation in healthcare.
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