C
Chao Zhang
Researcher at Beihang University
Publications - 4347
Citations - 118320
Chao Zhang is an academic researcher from Beihang University. The author has contributed to research in topics: Medicine & Computer science. The author has an hindex of 127, co-authored 3119 publications receiving 84711 citations. Previous affiliations of Chao Zhang include West Virginia University & University of Oklahoma.
Papers
More filters
Journal ArticleDOI
Comparison of laparoscopy-assisted and open radical gastrectomy for advanced gastric cancer: A retrospective study in a single minimally invasive surgery center.
TL;DR: LAG with radical LN dissection is a safe and technically feasible procedure for the treatment of AGC staged below T3 and the recurrence pattern and site were not different between the 2 groups, even they were stratified by the TNM stage.
Journal ArticleDOI
GeoBurst+: Effective and Real-Time Local Event Detection in Geo-Tagged Tweet Streams
TL;DR: GeoBurst+ as mentioned in this paper leverages a cross-modal authority measure to identify several pivots in the query window, which reveal different geo-topical activities and naturally attract similar tweets to form candidate events.
Journal ArticleDOI
Structural basis for the tethered peptide activation of adhesion GPCRs
Yuqi Ping,Peng Xiao,Fan Yang,Ru-Jia Zhao,Shengchao Guo,Xu Yan,Xiang Wu,Chao Zhang,Yan Lu,Fenghui Zhao,Fulai Zhou,Yue-Tong Xi,Wanchao Yin,Dongfang He,Dao-Lai Zhang,Zhongliang Zhu,Yi Jiang,Lutao Du,Shiqiong Feng,Torsten Schöneberg,Ines Liebscher,H. Eric Xu,Jingfen Sun +22 more
Proceedings ArticleDOI
Denoising Multi-Source Weak Supervision for Neural Text Classification.
TL;DR: A label denoiser is designed, which estimates the source reliability using a conditional soft attention mechanism and then reduces label noise by aggregating rule-annotated weak labels, which address the rule coverage issue.
Journal ArticleDOI
Modeling strategy for progressive failure prediction in lithium-ion batteries under mechanical abuse
TL;DR: This paper systematically studies the modeling approach for progressive failure simulation and short-circuit prediction, and provides useful insights on practical choices for the modeling strategy and safety design of LIBs under mechanical abuse conditions.