Construction of an XGBoost-SHAP-based malignant transformation risk prediction model for gallbladder polyps

Key Points

• The aim is to create and validate a model for predicting malignant transformation in gallbladder polyps (GBPs).
• Developed a prediction model using XGBoost technology.
• Validated the model for accuracy and clinical applicability.
• Integrated SHAP technology to enhance understanding of predictions.
• The model showed favorable discrimination and calibration for predicting malignant transformation.
• It demonstrated high accuracy, indicating reliable predictions for clinical use.
• The integration with SHAP technology improved treatment optimization.