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Machine learning-based insomnia symptom risk classification model for residents of Hebei province
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DOI：10.1016/j.puhe.2026.106409.png)
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Abstract
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The aim is to develop and externally validate a machine learning–based risk classification model for insomnia symptoms in a community-based population sample, and to identify and explain the main contributing factors using shapley additive explanations (SHAP).
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