The capability of deep-radiomics to predict pathological response to neoadjuvant immunochemotherapy in non–small cell lung cancer: a retrospective multicenter study

BackgroundTo establish a predictive model that combines radiomics, deep learning and clinical features for predicting the pathological complete response (pCR) of non-small cell lung cancer (NSCLC) patients after neoadjuvant immunochemotherapy (NIT).MethodsWe retrospectively collected patients from t...

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Autors principals:	Yuanxin Ye, Yuchi Tian, Lingling Wang, Zihan Xi, Yangfan Zhang, Tong Zhou, Zhenhua Zhao, Yifeng Zheng, Xiaoyun Liang, Haitao Jiang
Format:	Artigo
Idioma:	Inglês
Publicat:	Frontiers Media S.A. 2026-02-01
Col·lecció:	Frontiers in Immunology
Matèries:	deep learning delta-radiomics neoadjuvant immunochemotherapy NSCLC pathological complete response
Accés en línia:	https://www.frontiersin.org/articles/10.3389/fimmu.2026.1770042/full
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