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Complementing interpretable machine learning with synergistic analytical strategies for thyroid cancer recurrence

Souichi Oka1, Yoshiyasu Takefuji2

  • 1Science Park Corporation, 3-24-9 Iriya-Nishi Zama-shi, Kanagawa 252-0029, Japan.

European Journal of Radiology
|July 15, 2025
PubMed
Summary

High predictive accuracy in thyroid cancer recurrence models does not guarantee reliable feature importance. Integrative approaches combining machine learning with statistical methods are crucial for robust risk factor identification.

Keywords:
Feature importanceMachine LearningSHapley Additive exPlanationsStatistical validationThyroid Cancer Recurrence PredictionXGBoost

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