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The Crucial Role of Machine Learning Models in Predicting Current Childhood Asthma: Model Comparison, Calibration, and SHAP-Based Interpretation
Background: Asthma is one of the most prominent chronic diseases in children and one of the most challenging ailments to diagnose in infants and preschoolers in the United States. Predictive models can be instrumental in improving early diagnosis, personalized treatment strategies, and disease progr
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