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Dual-tracer PET Radiomics for Prostate Cancer Stratification
This single-center retrospective study aims to develop an interpretable radiomics model based on dual-tracer PET/CT to preoperatively predict the postoperative pathological Gleason grade group in treatment-naïve prostate cancer patients. A machine learning-based three-class prediction model will be constructed and interpreted using SHAP. Its performance will be compared with systematic biopsy results, assessing grading accuracy and prognostic value for biochemical recurrence-free survival.
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