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Explaining Risk Stratification in Differentiated Thyroid Cancer Using SHAP and Machine Learning Approaches
0
Zitationen
3
Autoren
2025
Jahr
Abstract
: The proposed interpretable neural network model effectively stratifies recurrence risk in DTC while reducing dependence on subjective pathological interpretation. SHAP-based feature attribution enhances clinical transparency, supporting integration of explainable machine learning into thyroid cancer follow-up and personalized management.
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