Preoperative identification of microvascular invasion in hepatocellular carcinoma by XGBoost and deep learning

PURPOSE: Microvascular invasion (MVI) is a valuable predictor of survival in hepatocellular carcinoma (HCC) patients. This study developed predictive models using eXtreme Gradient Boosting (XGBoost) and deep learning based on CT images to predict MVI preoperatively. METHODS: In total, 405 patients w...

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Detalhes bibliográficos
Publicado no:J Cancer Res Clin Oncol
Main Authors: Jiang, Yi-Quan, Cao, Su-E, Cao, Shilei, Chen, Jian-Ning, Wang, Guo-Ying, Shi, Wen-Qi, Deng, Yi-Nan, Cheng, Na, Ma, Kai, Zeng, Kai-Ning, Yan, Xi-Jing, Yang, Hao-Zhen, Huan, Wen-Jing, Tang, Wei-Min, Zheng, Yefeng, Shao, Chun-Kui, Wang, Jin, Yang, Yang, Chen, Gui-Hua
Formato: Artigo
Idioma:Inglês
Publicado em: Springer Berlin Heidelberg 2020
Assuntos:
Original Article – Clinical Oncology
Acesso em linha:https://ncbi.nlm.nih.gov/pmc/articles/PMC7873117/
https://ncbi.nlm.nih.gov/pubmed/32852634
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1007/s00432-020-03366-9
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