Zobrazeno 1 - 10
of 1 856
pro vyhledávání: '"TANG Juan"'
Autor:
Li Ying, Tang Juan, Li Changfen, Fang Qilin, Liu Xingde, Zhang Dan, Zhang Tingting, Wu Xiaoli, Li Tao
Publikováno v:
Guoji Yanke Zazhi, Vol 24, Iss 11, Pp 1708-1714 (2024)
AIM: To prepare a nanodrug MMC-ATS-@PLGA using polylactic acid hydroxyacetic acid copolymer(PLGA)as a carrier and mitomycin C(MMC)loaded on PLGA, and to analyse the biological safety and treatment effect of this nanodrug on inhibiting the proliferati
Externí odkaz:
https://doaj.org/article/c5da6b336b7947bc97343f3802ac98ca
Autor:
Tang Juan
Publikováno v:
Applied Mathematics and Nonlinear Sciences, Vol 9, Iss 1 (2024)
This paper firstly explores the method and monitoring process of coal SPC production quality monitoring based on IOT technology and simulates different control chart patterns using the Monte Carlo method. Then a control chart pattern recognition mode
Externí odkaz:
https://doaj.org/article/1862df142fa54c2ca959e0bdf9a7e2ee
Autor:
TANG Juan, LIU Zhiyan
Publikováno v:
Waike lilun yu shijian, Vol 26, Iss 06, Pp 504-509 (2021)
Externí odkaz:
https://doaj.org/article/e14ca690e57548e5836f61b2c243902d
Autor:
Xin Song, Wen-Qing Li, Nan Hu, Xue Ke Zhao, Zhaoming Wang, Paula L. Hyland, Tao Jiang, Guo Qiang Kong, Hua Su, Chaoyu Wang, Lemin Wang, Li Sun, Zong Min Fan, Hui Meng, Tang Juan Zhang, Ling Fen Ji, Shou Jia Hu, Wei Li Han, Min Jie Wu, Peng Yuan Zheng, Shuang Lv, Xue Min Li, Fu You Zhou, Laurie Burdett, Ti Ding, You-Lin Qiao, Jin-Hu Fan, Xiao-You Han, Carol Giffen, Margaret A. Tucker, Sanford M. Dawsey, Neal D. Freedman, Stephen J. Chanock, Christian C. Abnet, Philip R. Taylor, Li-Dong Wang, Alisa M. Goldstein
Publikováno v:
Scientific Reports, Vol 7, Iss 1, Pp 1-7 (2017)
Abstract Based on our initial genome-wide association study (GWAS) on esophageal squamous cell carcinoma (ESCC) in Han Chinese, we conducted a follow-up study to examine the single nucleotide polymorphisms (SNPs) associated with family history (FH) o
Externí odkaz:
https://doaj.org/article/ee819a9753a54ca2a0f945426e94214d
As is well known, differential algebraic equations (DAEs), which are able to describe dynamic changes and underlying constraints, have been widely applied in engineering fields such as fluid dynamics, multi-body dynamics, mechanical systems and contr
Externí odkaz:
http://arxiv.org/abs/2310.12846
Autor:
Wang, Lan, He, Ruiling, Zhao, Lili, Wang, Jia, Geng, Zhengzi, Ren, Tao, Zhang, Guo, Zhang, Peng, Tang, Kaiqiang, Gao, Chaofei, Chen, Fei, Zhang, Liting, Zhou, Yonghe, Li, Xin, He, Fanbin, Huan, Hui, Wang, Wenjuan, Liang, Yunxiao, Tang, Juan, Ai, Fang, Wang, Tingyu, Zheng, Liyun, Zhao, Zhongwei, Ji, Jiansong, Liu, Wei, Xu, Jiaojiao, Liu, Bo, Wang, Xuemei, Zhang, Yao, Yan, Qiong, Lv, Muhan, Chen, Xiaomei, Zhang, Shuhua, Wang, Yihua, Liu, Yang, Yin, Li, Liu, Yanni, Huang, Yanqing, Liu, Yunfang, Wang, Kun, Su, Meiqin, Bian, Li, An, Ping, Zhang, Xin, Qian, Linxue, Li, Shao, Qi, Xiaolong
Objective: Bleeding from gastroesophageal varices (GEV) is a medical emergency associated with high mortality. We aim to construct an artificial intelligence-based model of two-dimensional shear wave elastography (2D-SWE) of the liver and spleen to p
Externí odkaz:
http://arxiv.org/abs/2306.07505
Autor:
Xue Ke Zhao, Yi Min Mao, Hui Meng, Xin Song, Shou Jia Hu, Shuang Lv, Rang Cheng, Tang Juan Zhang, Xue Na Han, Jing Li Ren, Yi Jun Qi, Li Dong Wang
Publikováno v:
PLoS ONE, Vol 12, Iss 5, p e0177504 (2017)
Cancers from lung and esophagus are the leading causes of cancer-related deaths in China and share many similarities in terms of histological type, risk factors and genetic variants. Recent genome-wide association studies (GWAS) in Chinese esophageal
Externí odkaz:
https://doaj.org/article/bc5a560832644208bba147d132a4daa9
Publikováno v:
Kybernetes, 2022, Vol. 53, Issue 1, pp. 358-383.
Externí odkaz:
http://www.emeraldinsight.com/doi/10.1108/K-03-2022-0428
In real-world scenarios, many large-scale datasets often contain inaccurate labels, i.e., noisy labels, which may confuse model training and lead to performance degradation. To overcome this issue, Label Noise Learning (LNL) has recently attracted mu
Externí odkaz:
http://arxiv.org/abs/2203.10858
Publikováno v:
In LWT 1 October 2024 209