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This paper presents a machine learning approach to predict global obesity prevalence in children and adolescents up to the year 2050, utilizing various models including artificial neural networks, decision trees, and Naïve Bayes. The study highlights the alarming rise in obesity rates and associated health risks, with predictions indicating significant increases in diabetes, heart disease, and cancer cases linked to obesity. The research emphasizes the need for early intervention and effective frameworks to

Author

ieeeprocess

Language

EN