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Deep Segmentation Feature-Based Radiomics Improves Recurrence Prediction of Hepatocellular Carcinoma
Objective and Impact Statement. This study developed and validated a deep semantic segmentation feature-based radiomics (DSFR) model based on preoperative contrast-enhanced computed tomography (CECT) combined with clinical information to predict early recurrence (ER) of single hepatocellular carcino...
Autores principales: | Wang, Jifei, Wu, Dasheng, Sun, Meili, Peng, Zhenpeng, Lin, Yingyu, Lin, Hongxin, Chen, Jiazhao, Long, Tingyu, Li, Zi-Ping, Xie, Chuanmiao, Huang, Bingsheng, Feng, Shi-Ting |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
AAAS
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10521680/ https://www.ncbi.nlm.nih.gov/pubmed/37850181 http://dx.doi.org/10.34133/2022/9793716 |
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