An interpretable machine learning model for predicting survival in pancreatic cancer via SHAP: a multicenter study

Key Points

• Survival prediction in pancreatic cancer shows a significant increase in model interpretability with SHAP.
• The model achieves accurate predictions with over 85% effectiveness across multiple centers in assessing survival rates.
• Utilizing a machine learning approach enhanced by SHAP analysis, the model aims to improve clinical outcomes for patients.
• Future studies may confirm external applicability to larger populations with diverse profiles in pancreatic cancer.