Developed and validated a prognostic nomogram for recurrence-free survival after complete surgical resection of local primary gastrointestinal stromal tumors based on deep learning

Developed and validated a prognostic nomogram for recurrence-free survival after complete surgical resection of local primary gastrointestinal stromal tumors based on deep learning

This study aimed to develop and validate a prognostic nomogram for recurrence-free survival (RFS) after surgery in the absence of adjuvant therapy to guide the selection for adjuvant imatinib therapy based on Residual Neural Network (ResNet). The ResNet model was developed based on contrast-enhanced...

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Huvudupphovsmän: Tao Chen, Shangqing Liu, Yong Li, Xingyu Feng, Wei Xiong, Xixi Zhao, Yali Yang, Cangui Zhang, Yanfeng Hu, Hao Chen, Lin Tian, Mingli Zhao, Hao Liu, Jiang Yu, Yikai Xu, Yu Zhang, Guoxin Li
Materialtyp: Artigo
Språk:engelska
Publicerad: 2018
Länkar:https://doi.org/10.1016/j.ebiom.2018.12.028
http://www.thelancet.com/article/S2352396418306054/pdf
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https://doi.org/10.1016/j.ebiom.2018.12.028
http://www.thelancet.com/article/S2352396418306054/pdf

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