<ul><li>Researchers have developed a hybrid framework for enhancing metabolic syndrome (MetS) prediction.</li><li>The framework leverages advanced data balancing techniques and counterfactual analysis.</li><li>Multiple machine learning models were trained and compared under various data balancing techniques.</li><li>The study provides actionable insights for clinicians and researchers in mitigating the public health burden of MetS.</li></ul>

Enhancing Metabolic Syndrome Prediction with Hybrid Data Balancing and Counterfactuals

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