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Murat Yüce

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Open access Sep 2026

Comparing clinicopathological factors and quantitative background parenchymal enhancement to predict pathological complete response after neoadjuvant chemotherapy in breast cancer.

PURPOSE To investigate the predictive value of deep learning (nnU-Net)-based fully automated quantitative background parenchymal enhancement (BPE) metrics and clinicopathological factors for pathological complete response (pCR) in patients with breast cancer receiving neoadjuvant chemotherapy (NACT). METHODS This ret...

Süleyman Öncü, Murat Yüce, Ahmet İrfan Temur · 0 citations

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