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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Publicado en:J Cancer Res Clin Oncol
Autores principales: 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
Lenguaje:Inglês
Publicado: Springer Berlin Heidelberg 2020
Materias:
Original Article – Clinical Oncology
Acceso en línea: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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