Zobrazeno 1 - 9
of 9
pro vyhledávání: '"Shijian Ruan"'
Autor:
Wenjie Liang, Wuwei Tian, Yifan Wang, Pan Wang, Yubizhuo Wang, Hongbin Zhang, Shijian Ruan, Jiayuan Shao, Xiuming Zhang, Danjiang Huang, Yong Ding, Xueli Bai
Publikováno v:
BMC Cancer, Vol 22, Iss 1, Pp 1-10 (2022)
Abstract Background Preoperative prediction of pancreatic cystic neoplasm (PCN) differentiation has significant value for the implementation of personalized diagnosis and treatment plans. This study aimed to build radiomics deep learning (DL) models
Externí odkaz:
https://doaj.org/article/8d111222bf1c4c41b426eac5aa91b35e
Autor:
Lintao Chen, Shijian Ruan, Pan Wang, Yongna Cheng, Yubizhuo Wang, Wuwei Tian, Hongbin Zhang, Xiuming Zhang, Wenjie Liang
Publikováno v:
Heliyon, Vol 9, Iss 3, Pp e14123- (2023)
Purpose: Primary hepatic sarcomatoid carcinoma (PHSC) is a rare type of malignant tumor in the liver. Nevertheless, few studies have focused on the imaging diagnosis of PHSC. In this study, we collected clinical and computed tomography (CT) imaging d
Externí odkaz:
https://doaj.org/article/7b2e6e64270d4700a10ee1df683bccc5
Autor:
Yong Ding, Shijian Ruan, Yubizhuo Wang, Jiayuan Shao, Rui Sun, Wuwei Tian, Nan Xiang, Weigang Ge, Xiuming Zhang, Kunkai Su, Jingwen Xia, Qiang Huang, Weihai Liu, Qinxue Sun, Haibo Dong, Mylène C. Q. Farias, Tiannan Guo, Andrey S. Krylov, Wenjie Liang, Wenbo Xiao, Xueli Bai, Tingbo Liang
Publikováno v:
Clinical and Translational Medicine, Vol 11, Iss 11, Pp n/a-n/a (2021)
Externí odkaz:
https://doaj.org/article/7d08af4ccace4c098793973fdff89429
Autor:
Yubizhuo Wang, Jiayuan Shao, Pan Wang, Lintao Chen, Mingliang Ying, Siyuan Chai, Shijian Ruan, Wuwei Tian, Yongna Cheng, Hongbin Zhang, Xiuming Zhang, Xiangming Wang, Yong Ding, Wenjie Liang, Liming Wu
Publikováno v:
Frontiers in Oncology, Vol 11 (2021)
BackgroundOur aim was to establish a deep learning radiomics method to preoperatively evaluate regional lymph node (LN) staging for hilar cholangiocarcinoma (HC) patients. Methods and MaterialsOf the 179 enrolled HC patients, 90 were pathologically d
Externí odkaz:
https://doaj.org/article/c0bdf032661741758054ca28615c7097
Autor:
Wenjie Liang, Jiayuan Shao, Weihai Liu, Shijian Ruan, Wuwei Tian, Xiuming Zhang, Dalong Wan, Qiang Huang, Yong Ding, Wenbo Xiao
Publikováno v:
Frontiers in Oncology, Vol 10 (2020)
Background: We conduct a study in developing and validating two radiomics-based models to preoperatively distinguish hepatic epithelioid angiomyolipoma (HEAML) from hepatic carcinoma (HCC) as well as focal nodular hyperplasia (FNH).Methods: Totally,
Externí odkaz:
https://doaj.org/article/c852e40adb9542779f25da200df0063f
Autor:
Xiuming Zhang, Shijian Ruan, Wenbo Xiao, Jiayuan Shao, Wuwei Tian, Weihai Liu, Zhao Zhang, Dalong Wan, Jiacheng Huang, Qiang Huang, Yunjun Yang, Hanjin Yang, Yong Ding, Wenjie Liang, Xueli Bai, Tingbo Liang
Publikováno v:
Clinical and Translational Medicine, Vol 10, Iss 2, Pp n/a-n/a (2020)
Abstract Background The present study constructed and validated the use of contrast‐enhanced computed tomography (CT)‐based radiomics to preoperatively predict microvascular invasion (MVI) status (positive vs negative) and risk (low vs high) in p
Externí odkaz:
https://doaj.org/article/d42ee7728c544c89a3040eb7d771905f
Autor:
Andrey S. Krylov, Wuwei Tian, Xueli Bai, Jiayuan Shao, Tingbo Liang, Nan Xiang, Kunkai Su, Xiuming Zhang, Qiang Huang, Qinxue Sun, Tiannan Guo, Wenbo Xiao, Haibo Dong, Wenjie Liang, Yubizhuo Wang, Weihai Liu, Rui Sun, Weigang Ge, Jingwen Xia, Mylène C. Q. Farias, Yong Ding, Shijian Ruan
Publikováno v:
Clinical and Translational Medicine
Clinical and Translational Medicine, Vol 11, Iss 11, Pp n/a-n/a (2021)
Clinical and Translational Medicine, Vol 11, Iss 11, Pp n/a-n/a (2021)
Autor:
Weigang Ge, Jingwen Xia, Jiayuan Shao, Xueli Bai, Tingbo Liang, Andrey S. Krylov, Kunkai Su, Qiang Huang, Shijian Ruan, Weihai Liu, Nan Xiang, Qinxue Sun, Wenbo Xiao, Yong Ding, Rui Sun, Haibo Dong, Wenjie Liang, Tiannan Guo, Wuwei Tian, Xiuming Zhang, Mylène C. Q. Farias
Publikováno v:
SSRN Electronic Journal.
Background: The evaluation of tumor differentiation is an urgent clinical issue that would facilitate the establishment of individualized therapeutic strategies. Our aims were to develop a deep learning radiomics model based on computed tomography (C
Autor:
Yunjun Yang, Qiang Huang, Wenbo Xiao, Weihai Liu, Xueli Bai, Yong Ding, Tingbo Liang, Xiuming Zhang, Shijian Ruan, Wuwei Tian, Wenjie Liang, Zhao Zhang, Dalong Wan, Hanjin Yang, Jiacheng Huang, Jiayuan Shao
Publikováno v:
Clinical and Translational Medicine
Clinical and Translational Medicine, Vol 10, Iss 2, Pp n/a-n/a (2020)
Clinical and Translational Medicine, Vol 10, Iss 2, Pp n/a-n/a (2020)
Background The present study constructed and validated the use of contrast‐enhanced computed tomography (CT)‐based radiomics to preoperatively predict microvascular invasion (MVI) status (positive vs negative) and risk (low vs high) in patients w