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A Decision Tree Ensemble Approach to Diabetes Prediction using the Framingham Heart Dataset, Exploring the Role of AI-Associated Interventions in Reducing Diabetes-Related Adverse Outcomes Between Men and Women
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3
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2025
Jahr
Abstract
ObjectiveDiabetes poses significant public health challenges, with many individuals remaining undiagnosed and at risk of complications.This study aimed to evaluate the performance of decision tree ensemble methods for predicting diabetes onset using the Framingham Heart Study Teaching Dataset and to explore sex-specific risk patterns relevant to AI-driven interventions. MethodsWe analyzed data from 11,627 participants, incorporating demographics, vital signs, smoking status, medication use, and laboratory measures.Random Forest classifiers were developed to predict diabetes incidence at 2025 Ranjani Anirudhan, et al.
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