What question did this study set out to answer?

The aim is to create and validate a model for predicting malignant transformation in gallbladder polyps (GBPs).

April 26, 2026Open Access

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

WLWen-Hui LuoYuhuangding Hospital MCMeng-Han CaiTianjin University of Traditional Chinese Medicine YWYu WangJining Medical University

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.

Abstract

This study developed and validated a risk prediction model for malignant transformation in patients with GBPs. The model demonstrated favorable discrimination, calibration, accuracy, and clinical applicability. Integration with SHAP technology may assist clinicians in optimizing treatment and management strategies.

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