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12篇 您的检索式:作者名="Jian‐Yu Li"
    题名 作者 年代 出处 被引量
1Overexpression of BMI ‐1 is associated with poor prognosis in cervical cancer显示文摘Yong‐Qing Tong Bei Liu Hong‐Yun Zheng Yu‐Juan He Jian Gu Feng Li Yan Li 2012Asia‐Pac J Clin Oncol2012,,4:1
2Overexpression of BMI ‐1 is associated with poor prognosis in cervical cancer显示文摘Yong‐Qing Tong Bei Liu Hong‐Yun Zheng Yu‐Juan He Jian Gu Feng Li Yan Li 2012Asia‐Pac J Clin Oncol2012,,4:1
3Scale adaptive fitness evaluation‐based particle swarm optimisation for hyperparameter and architecture optimisation in neural networks and deep learning显示文摘Research into automatically searching for an optimal neural network(NN)by optimi-sation algorithms is a significant research topic in deep learning and artificial intelligence.However,this is still challenging due to two issues:Both the hyperparameter and ar-chitecture should be optimised and the optimisation process is computationally expen-sive.To tackle these two issues,this paper focusses on solving the hyperparameter and architecture optimization problem for the NN and proposes a novel light‐weight scale‐adaptive fitness evaluation‐based particle swarm optimisation(SAFE‐PSO)approach.Firstly,the SAFE‐PSO algorithm considers the hyperparameters and architectures together in the optimisation problem and therefore can find their optimal combination for the globally best NN.Secondly,the computational cost can be reduced by using multi‐scale accuracy evaluation methods to evaluate candidates.Thirdly,a stagnation‐based switch strategy is proposed to adaptively switch different evaluation methods to better balance the search performance and computational cost.The SAFE‐PSO algorithm is tested on two widely used datasets:The 10‐category(i.e.,CIFAR10)and the 100−cate-gory(i.e.,CIFAR100).The experimental results show that SAFE‐PSO is very effective and efficient,which can not only find a promising NN automatically but also find a better NN than compared algorithms at the same computational cost.Ye‐Qun Wang Jian‐Yu Li Chun‐Hua Chen Jun Zhang Zhi‐Hui Zhan 2023CAAI Transactions on Intelligence Technology2023,8,3:0
4Synergistic effects of ultrashort wave and bone marrow stromal cells on nerve regeneration with acellular nerve allografts显示文摘Chao‐jian Pang Lei Tong Li‐li Ji Zhen‐yu Wang Xu Zhang Hai Gao Hua Jia Li‐xin Zhang Xiao‐jie Tong 2013Synapse2013,,10:1
5Tumor‐associated macrophages promote angiogenesis and lymphangiogenesis of gastric cancer显示文摘Hui Wu Jian‐Bo Xu Yu‐Long He Jian‐Jun Peng Xin‐Hua Zhang Chuang‐Qi CHEN Wen Li Shi‐Rong Cai 2012J. Surg. Oncol2012,,4:1
6TNF ‐α Upregulates Fgl2 Expression in Rat Myocardial Ischemia/Reperfusion Injury显示文摘Peng Jia Jue Wang Li Wang Xin Chen Yu Chen Wen‐Zhu Li Rui Long Jian Chen Yan‐Wen Shu Kun Liu Zhao‐Hui Wang 2013Microcirculation2013,,6:1
7Nitrous Oxide‐Oxygen Mixture During Burn Wound Dressing: A Double‐Blind Randomized Controlled Study显示文摘Yu‐Xiang Li Wen‐Jun Han Hong‐Tai Tang Yin‐Sheng Wu Lu Tang Jian‐Qiang Yu Yan‐Cang Li Zhao‐Fan Xia Ji‐Jun Zhao 2013CNS Neurosci Ther2013,,:1
8Acute metformin preconditioning confers neuroprotection against focal cerebral ischaemia by pre‐activation of AMPK ‐dependent autophagy显示文摘Teng Jiang Jin‐Tai Yu Xi‐Chen Zhu Hui‐Fu Wang Meng‐Shan Tan Lei Cao Qiao‐Quan Zhang Li Gao Jian‐Quan Shi Ying‐Dong Zhang Lan Tan 2014Br J Pharmacol2014,,13:1
9Arabidopsis acyl‐ C o A ‐binding protein ACBP 3 participates in plant response to hypoxia by modulating very‐long‐chain fatty acid metabolism显示文摘Li‐Juan Xie Lu‐Jun Yu Qin‐Fang Chen Feng‐Zhu Wang Li Huang Fan‐Nv Xia Tian‐Ren Zhu Jian‐Xin Wu Jian Yin Bin Liao Nan Yao Wensheng Shu Shi Xiao 2015Plant J2015,,1:1
10Controlled attenuation parameter for the detection of steatosis severity in chronic liver disease: A meta‐analysis of diagnostic accuracy显示文摘Ke‐Qing Shi Jun‐Zhou Tang Xue‐Lian Zhu Li Ying De‐Wei Li Jian Gao Yu‐Xiao Fang Gui‐Ling Li Yi‐Jiang Song Zhu‐Jun Deng Jian‐Min Wu Kai‐Fu Tang 2014J Gastroenterol Hepatol2014,,6:1
11Reversal of hepatocyte senescence after continuous in vivo cell proliferation显示文摘Min‐Jun Wang Fei Chen Jian‐Xiu Li Chang‐Cheng Liu Hai‐Bin Zhang Yong Xia Bing Yu Pu You Dao Xiang Lian Lu Hao Yao Uyunbilig Borjigin Guang‐Shun Yang Kirk J. Wangensteen Zhi‐Ying He Xin Wang Yi‐Ping Hu 2014Hepatology2014,,1:1
12Tolerance and acceptance of hepatic venous pressure gradient measurement in cirrhosis(CHESS1904):An international multicenter study显示文摘Aim:To determine the tolerance and acceptance of hepatic venous pressure gradient(HVPG)measurements in patients with liver cirrhosis.Methods:This prospective international multicenter study included 271 patients with cirrhosis who were scheduled to undergo HVPG measurement between October 2019 and June 2020.Data related to the tolerance and acceptance of HVPG measurements were collected using descriptive questionnaires.Results:HVPG measurements were technically successful in all 271 patients,with 141(52.0%)undergoing HVPG measurement alone.The complication rate was 0.4%.Postoperative pain was significantly lower than preoperative expected pain(p<0.001)and intraoperative pain(p<0.001),and intraoperative pain was also significantly lower than preoperative expected pain(p=0.036).No,mild,moderate,severe,and intolerable discomfort scores were reported by 36.9%,44.6%,11.1%,6.3%,and 0.4%of these patients,respectively,during HVPG measurement and by 54.6%32.5%,11.4%,1.5%,and 0%,respectively,after HVPG measurement.Of these patients,39.5%had little understanding and 10%had no understanding of the value of HVPG measurement,with 35.1%and 4.1%regarding HVPG measurements as being of little or no help,respectively.Most patients reported that they would definitely(15.5%),probably(46.9%),or possibly(29.9%)choose to undergo additional HVPG measurements again,and 62.7%regarded the cost of the procedure as acceptable.Conclusion:HVPG measurement was safe and well‐tolerated in patients with cirrhosis,but patient education and communication are warranted to improve the acceptance of this procedure.Jun‐Hui Sun He Zhao Haijun Zhang Lei Li NecatiÖrmeci Zi‐Niu Yu Xun Li Shuangxi Li Xujun Yang Huaping Wei Xiaoliang Zhu Zhengcong Zhang Yajin Wang Zhongwei Zhao Jianting Mao Qiaohong Wu Xiaole Sun Huiling Xiang Kefeng Jia Chao Yang Wei Wu Xiuqing Lin Haixin Yao Changzeng Zuo Jitao Wang Bo Zhang Chunqing Zhang Xiaoling Wu Guangchuan Wang Shengjuan Yao Ruihang Wang Li Zhou Hui Huan Qingli Tu Xue Pu Feng Zhang Qin Yin Linpeng Zhang Ying Guo Jian Wang Kohei Kotani Sawako Uchida‐Kobayashi Norifumi Kawada He Zhu Li Li Wei Wang Guo Zhang Lei Yu Xudong Cui Qingliang Zhu Hailong Zhang Xiaoli Hu Rafael OXimenes Adriano Gonçalves de Araújo Giulliano Gardenghi Yubao Zheng Zebin Wu Mingsheng Huang Xiaoyong Chen Jun Wu Feng Xie Yang Bo Shengjuan Hu Linke Ma Xiao Li Xiaolong Qi 2022Portal Hypertension & Cirrhosis2022,1,1:0
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