Integrated model improves prediction accuracy in bladder cancer patients, suggesting better treatment strategies through deep learning and interpretable methodologies.
The integrated model, combining DECT quantitative parameters, habitat features, and 2.5D DL features, enhances the accuracy of preoperative predictions for muscle invasion status in BCa. The SHAP methodology improves the interpretability of decision-making within the model and provides valuable support for clinicians in developing personalized treatment strategies.
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He et al. (2025) studied this question.
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