Zobrazeno 1 - 10
of 19
pro vyhledávání: '"Yi-Quan Jiang"'
Autor:
Zhi-Mei Huang, Xue Han, Jian Wang, Ling Gu, Lu Tang, Shao-Yong Wu, Tian Di, Ying-Wen Hou, Wan Yee Lau, Yi-Quan Jiang, Jin-Hua Huang
Publikováno v:
Liver Cancer, Pp 1-13 (2024)
Introduction: For patients with large unresectable hepatocellular carcinoma (HCC), the effectiveness of conventional transarterial chemoembolization (cTACE) remains suboptimal. This study investigated the efficacy and safety of modified TACE using lo
Externí odkaz:
https://doaj.org/article/c8867ce335db4e1c8405b9245905b46a
Autor:
Yi-Quan Jiang, Zi-Xian Wang, Ming Zhong, Lu-Jun Shen, Xue Han, Xuxiazi Zou, Xin-Yi Liu, Yi-Nan Deng, Yang Yang, Gui-Hua Chen, Wuguo Deng, Jin-Hua Huang
Publikováno v:
OncoImmunology, Vol 10, Iss 1 (2021)
Currently, a significant proportion of cancer patients do not benefit from programmed cell death-1 (PD-1)-targeted therapy. Overcoming drug resistance remains a challenge. In this study, single-cell RNA sequencing and bulk RNA sequencing data from sa
Externí odkaz:
https://doaj.org/article/69931149762342a5b49c13e2823b4304
Publikováno v:
Frontiers in Oncology, Vol 9 (2019)
Background: Because of the poor health conditions of elderly patients (age >65) with very-early-stage and early-stage hepatocellular carcinoma (HCC), primary treatment via hepatic resection (HR), or radiofrequency ablation (RFA) must be considered. H
Externí odkaz:
https://doaj.org/article/bb0aa1db64ef4253a0f7eb80b3b0d5fb
Autor:
Hong Liang Zou, Hui Tang, Chao An, Lu Jun Shen, Ji Bin Li, Wan Yee Lau, Yi Quan Jiang, Jin Hua Huang
Publikováno v:
World Journal of Oncology. 14:125-134
Autor:
Yinan Deng, Guoying Wang, Kaining Zeng, Na Cheng, Xi-Jing Yan, Yi-Quan Jiang, Wei-Min Tang, Jian-ning Chen, Wen-Jing Huan, Wen-Qi Shi, Gui-hua Chen, Yang Yang, Kai Ma, Yefeng Zheng, Shilei Cao, Yang Haozhen, Chun-Kui Shao, Su-E Cao, Jin Wang
Publikováno v:
Journal of Cancer Research and Clinical Oncology
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
Publikováno v:
Proceedings of the International Field Exploration and Development Conference 2021 ISBN: 9789811921483
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f89e4774034b9aabc971cb6a7206d559
https://doi.org/10.1007/978-981-19-2149-0_414
https://doi.org/10.1007/978-981-19-2149-0_414
Autor:
Yi-Quan Jiang, Yiming Huang, Haibo Li, Tong Zhang, Kaining Zeng, Yusheng Cheng, Tingting Xia, Yang Yang, Yinan Deng
Publikováno v:
Liver Research, Vol 3, Iss 3, Pp 240-249 (2019)
Background: Abnormal expression of long non-coding RNAs (lncRNAs) has been found in almost all tumors in humans, providing numerous potential diagnostic and prognostic biomarkers, and therapeutic targets. Materials and methods: The Cancer Genome Atla
Autor:
Binkui Li, Yun Zheng, Yanping Ma, Jiliang Qiu, Yunfei Yuan, Zining Xu, Guoying Wang, Zhiyu Qiu, Zhentao Yu, Lujun Shen, Wei He, Mengting Shi, Yi-Quan Jiang
Publikováno v:
Ann Transl Med
BACKGROUND: The combination of transarterial chemoembolization (TACE) with sorafenib has demonstrated superior efficacy over sorafenib and TACE monotherapy in hepatocellular carcinoma (HCC). Apatinib, a new targeted agent, has been recently reported
Autor:
Jinhua Huang, Zi-Xian Wang, Wuguo Deng, Yinan Deng, Yang Yang, Xue Han, Xuxiazi Zou, Ming Zhong, Lujun Shen, Yi-Quan Jiang, Guihua Chen, Xin-Yi Liu
Publikováno v:
Oncoimmunology
article-version (VoR) Version of Record
OncoImmunology, Vol 10, Iss 1 (2021)
article-version (VoR) Version of Record
OncoImmunology, Vol 10, Iss 1 (2021)
Currently, a significant proportion of cancer patients do not benefit from programmed cell death-1 (PD-1)-targeted therapy. Overcoming drug resistance remains a challenge. In this study, single-cell RNA sequencing and bulk RNA sequencing data from sa
Publikováno v:
Frontiers in Oncology, Vol 10 (2020)
Frontiers in Oncology
Frontiers in Oncology
Aim: To assess the ablative margin (AM) after microwave ablation (MWA) for hepatocellular carcinoma (HCC) with a deep learning-based deformable image registration (DIR) technique and analyze the relation between the AM and local tumor progression (LT