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Based on pre-treatment and early treatment dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and clinical characteristics, we established a pathological complete response (pCR) prediction model using a deep learning radiomic (DLR) method that achieved good performance in the training and validation cohorts. The model can help clinicians evaluate whether the patient can reach pCR after neoadjuvant chemotherapy (NAC) and can provide an effective diagnostic reference for accurate medical treatment of patients receiving NAC.
Yang et al. (Wed,) studied this question.
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