Fig 1.
Schematic representation of the development of the prediction model.
SMOTE: Synthetic Minority Over-Sampling Technique.
Table 1.
Socio-demographic characteristic train set (2002 to 2010).
Table 2.
Socio-demographic Characteristic Sex-specific Test Set (2011 to 2019).
Fig 2.
Area Under the Receiver Characteristics Curve (AUROC).
Discriminatory performance of models A: the area under the receiver characteristics curve (AUROC) of men; B: the area under the receiver characteristics curve (AUROC) of women.
Table 3.
Models performance.
Fig 3.
Feature importance of the logistic regression model.
The 20 most important features in the LR model with sex-specific A: men model and B: women model.
Fig 4.
SHAP summary plot for the XGBoost-based suicide prediction model.
The 20 most important SHAP-value with sex-specific A: men model and B: women model.