Predicting depression and anxiety of Chinese population during COVID-19 in psychological evaluation data by XGBoost

Journal of Affective Disorders(2023)

Cited 5|Views13
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Abstract
•Our extreme gradient boosting (Xgboost) model showed good performance for predicting depression and anxiety.•Optimism and presence of social support are important factors for identifying depression and anxiety.•After feature selection, the model with 19 variables simplifies the whole process compared with the model with 56 variables.
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Key words
Machine learning,Depression,Anxiety,Resilience,Social support,COVID-19 pandemic
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