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Your search keyword '"Lian, Mengjia"' showing total 24 results
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24 results on '"Lian, Mengjia"'

6. Underestimated disease prevalence and severe phenotypes in patients with biallelic variants: A cohort study of primary familial brain calcification from China

Author

Huang, Xuerong, Fu, Shaowei, Chen, Wenhai, Huang, Yanbin, Lan, Likang, Zhu, Xiaofen, Xu, Zhijun, Huang, Huayun, Zhou, Lifeng, Chen, Zilong, Lou, Minfang, Wang, Binglan, Tan, Yi, Zhu, Manlian, Hong, Weijun, Wang, Feng, Pan, Gonghua, Shao, Aimin, Li, Weiying, Li, Haijun, Zhao, Na, Hu, Haoyu, Zhang, Yaxi, Lian, Mengjia, Li, Jieying, Cai, Xueli, Luo, Zixian, Zhou, Yan, Lu, Xiaoyi, Ma, Li, Xia, Enkui, Zhang, Xiaoluo, Chen, Si, Cen, Zhidong, Fu, Feng, Chen, You, Chen, Xinhui, Yang, Dehao, Wang, Haotian, Wu, Hongwei, Zheng, Xiaosheng, Xie, Fei, Ouyang, Zhiyuan, Tang, Weiguo, Zhang, Shuhong, Yin, Lili, Zhang, Yunqian, Meng, Peiying, Zhu, Xuzhen, Zhang, Hongwei, Jiang, Feifei, Zhang, Kaiyu, He, Juping, Zhang, Danhong, Ming, Hanqiao, Song, Daqiao, Zhou, Zhiping, Luo, Yong, Gu, Qun, Su, Yongkun, Wu, Xinxiao, Tang, Haiyan, Wu, Chenglong, Chen, Weiqing, Liu, Jing-Yu, and Luo, Wei

Published
2019
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12. Visualization Analysis of Multidimensional Data for Online Transaction Log

Author

Yu Shidong, Yang Dong-sheng, Lian Mengjia, and Feng Xue

Subjects
Sequence, Geospatial analysis, Computer science, Transaction log, Data mining, Space (commercial competition), computer.software_genre, Transaction data, computer, Parallel coordinates, Visualization, Hierarchical clustering
Abstract

The online transaction data presents significant multi-dimensional and spatiotemporal attributes. The existing visualization methods cannot fully combine the time series, hierarchical, geospatial and multi-dimensional features of online transaction log to perform multi-aspect analysis on commodity sales. Therefore, this paper proposes a collaborative visualization method for multi-dimensional and spatiotemporal data. The attribute collaborative view is designed to present the multi-dimensional properties and their relationships of spatial objects of interest. By means of multi-dimensional scaling, the original dataset is degraded to one-dimensional space in a chronological order, which further enable the construction of the sequence parallel coordinates. In order to enhance the visual perception of the parallel coordinates, the coordinate axes are scaled, so the sparse areas are compressed and the dense areas are stretched. Hierarchical clustering is used to further analyze the display results of parallel coordinates, and the temporal features of different categories can be found more clearly. It can be concluded that the proposed method is able to help users quickly explore the characteristic patterns hidden in the multi-dimensional and spatiotemporal dataset through the actual case study of online transaction data.

Published
2019

18. Underestimated disease prevalence and severe phenotypes in patients with biallelic variants: A cohort study of primary familial brain calcification from China

Author

Chen, Si, primary, Cen, Zhidong, additional, Fu, Feng, additional, Chen, You, additional, Chen, Xinhui, additional, Yang, Dehao, additional, Wang, Haotian, additional, Wu, Hongwei, additional, Zheng, Xiaosheng, additional, Xie, Fei, additional, Ouyang, Zhiyuan, additional, Tang, Weiguo, additional, Zhang, Shuhong, additional, Yin, Lili, additional, Zhang, Yunqian, additional, Meng, Peiying, additional, Zhu, Xuzhen, additional, Zhang, Hongwei, additional, Jiang, Feifei, additional, Zhang, Kaiyu, additional, He, Juping, additional, Zhang, Danhong, additional, Ming, Hanqiao, additional, Song, Daqiao, additional, Zhou, Zhiping, additional, Luo, Yong, additional, Gu, Qun, additional, Su, Yongkun, additional, Wu, Xinxiao, additional, Tang, Haiyan, additional, Wu, Chenglong, additional, Chen, Weiqing, additional, Liu, Jing-Yu, additional, Luo, Wei, additional, Huang, Xuerong, additional, Fu, Shaowei, additional, Chen, Wenhai, additional, Huang, Yanbin, additional, Lan, Likang, additional, Zhu, Xiaofen, additional, Xu, Zhijun, additional, Huang, Huayun, additional, Zhou, Lifeng, additional, Chen, Zilong, additional, Lou, Minfang, additional, Wang, Binglan, additional, Tan, Yi, additional, Zhu, Manlian, additional, Hong, Weijun, additional, Wang, Feng, additional, Pan, Gonghua, additional, Shao, Aimin, additional, Li, Weiying, additional, Li, Haijun, additional, Zhao, Na, additional, Hu, Haoyu, additional, Zhang, Yaxi, additional, Lian, Mengjia, additional, Li, Jieying, additional, Cai, Xueli, additional, Luo, Zixian, additional, Zhou, Yan, additional, Lu, Xiaoyi, additional, Ma, Li, additional, Xia, Enkui, additional, and Zhang, Xiaoluo, additional

Published
2019
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24. Diagnostic, monitoring, and prognostic value of combined detection of lactate dehydrogenase, β2-transferrin, and interleukin-10 for acute intracranial infections.

Author

Feng Z, Liu X, Lian M, and Zhang L

Abstract

Objective: To investigate the value of the combined detection of lactate dehydrogenase (LDH), β2-transferrin (β-2Tf), and interleukin-10 (IL-10) for identification of acute intracranial infections such as meningitis., Methods: A total of 103 patients were placed in the suppurative meningitis group (SMG), 124 patients in the viral meningitis group (VMG). Another 86 patients without any infectious diseases of the central nervous system constituted the control group (CG). The levels of LDH and β-2Tf in the cerebrospinal fluid were determined by enzymatic methods; IL-10 expression was measured by ELISA. The correlation between infection and the LDH, β-2Tf, and IL-10 levels was analyzed by linear correlation analysis, and ROC curve analysis was applied to determine the diagnostic value of combined detection of LDH, β-2Tf, and IL-10 levels for intracranial infections., Results: LDH, β-2Tf, and IL-10 levels negatively correlated with the treatment time in both the SMG (r = -0.52, -0.97, and -0.24, respectively, P < 0.01) and VMG (r = -0.70, -0.91, and -0.25, respectively, P < 0.01). Sensitivity and specificity of combined detection of LDH, β-2Tf, and IL-10 for the diagnosis of SM was 80.47% and 75.33%, respectively, while those for VM were 84.24% and 79.24%, respectively., Conclusion: Combined detection is an excellent indicator for the diagnosis and treatment of intracranial infections., Competing Interests: None., (AJTR Copyright © 2021.)

Published
2021

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