https://orcid.org/0009-0003-2716-7505
Figures & data
Figure 1 Data Processing and Analysis Flowchart.
Table 1 Baseline Characteristics of the Population in the Training Set
Table 2 Performance Evaluation of Six Machine Learning Prediction Models Using 31 Indicators
Figure 2 ROC curves for the validation set model with 31 indicators.
Table 3 Results of ML Models for Feature Selection
Figure 3 Ranking of feature importance in three machine learning model. (a) Ranking of feature importance in the RF model, (b) Ranking of feature importance in the XGBoost model, (c) Ranking of feature importance in the LightGBM model.
Table 4 Performance Evaluation of Six Machine Learning Prediction Models Using 8 Indicators
Figure 4 ROC curves for the validation set model with 8 indicators.
Table 5 Performance Evaluation of Six Machine Learning Prediction Models Using 3 Indicators
Figure 5 ROC curves for the validation set model with 3 indicators.
Figure 6 SHAP of the LightGBM model.
Table 6 Subgroup Analysis Using LightGBM Model
Figure 7 (a–j) The ROC curves for subgroup analysis based on the LightGBM model.
Data Sharing Statement
The author will provide raw data that supports the conclusions of this article without reservation. Requests to access these datasets should be directed to T.W. (Tingting Wang), [email protected].