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BACKGROUND Accurate preoperative staging and identification of adverse pathological features in upper tract urothelial carcinoma (UTUC) remain contemporary challenges. We aimed to develop and internally validate machine-learning (ML) models to predict muscle-invasive (≥pT2) and lymph node positive (pN+) disease using p...
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