Diabetes and Stroke Prediction using NHANES Data

The project “Diabetes and Stroke Prediction using NHANES Data” uses extensive data from the National Health and Nutrition Examination Survey (NHANES) to develop predictive models for diabetes and stroke risk. By analyzing lifestyle factors such as diet, physical activity, smoking, and alcohol consumption, the project aims to identify key predictors of diabetes and stroke. The study employs advanced techniques like RandomForestClassifier and XGBoost to handle large datasets and improve prediction accuracy. The findings provide valuable insights for healthcare providers and policymakers, offering evidence-based recommendations for preventive strategies and personalized interventions to tackle these significant public health issues. You can find the codebase on GitHub.