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18 results on '"Yuan, Kehua"'

8. Feature Selection Using Zentropy-Based Uncertainty Measure

Author

Yuan, Kehua, Miao, Duoqian, Yao, Yiyu, Zhang, Hongyun, and Zhao, Xuerong

Abstract

Feature selection and entropy theory are two efficacious data analysis tools for investigating uncertainty information processing in artificial intelligence. The fruitful marriage of the two has been an active research topic in knowledge discovery. Currently, most feature selection methods via entropy theory mainly focus on the information measures at a single granular level. However, it ignores the interaction between granular levels, which leads to the poor stability and accuracy of related methods. Hence, this article proposes a novel zentropy-based uncertainty measure to design a feature selection method by exploiting the granular level structure in knowledge space. Subsequently, by analyzing the granular level structure in decision data, the zentropy-based uncertainty measure and its properties are designed and analyzed to depict the uncertainty knowledge from whole and internal. Moreover, two importance measures are defined to evaluate features based on the designed uncertainty measure, and then a corresponding feature selection algorithm is developed. Finally, some experiments are carried out on public datasets to demonstrate that the proposed method can achieve state-of-the-art performance among methods, especially regarding stability and classification accuracy.

Published
2024
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9. Using Fuzzy Cognitive Map to Effectively Classify E-Documents and Application

Author

Wang, Jianzeng, Xing, Yunpeng, Shi, Peng, Guo, Fei, Wang, Zhen, Yao, Erlin, Yuan, Kehua, Zhang, Junsheng, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Dough, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Zhuge, Hai, editor, and Fox, Geoffrey C., editor

Published
2005
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10. The Architecture and Implementation of Resource Space Model System

Author

Shi, Peng, Xing, Yunpeng, Yao, Erlin, Wang, Zhen, Yuan, Kehua, Zhang, Junsheng, Wang, Jianzeng, Guo, Fei, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Dough, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Zhuge, Hai, editor, and Fox, Geoffrey C., editor

Published
2005
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15. LncRNA CRNDE and lncRNA SNHG7 are Promising Biomarkers for Prognosis in Synchronous Colorectal Liver Metastasis Following Hepatectomy

Author

Zhang, Peixian, Shi, Lan, Song, Linjing, Long, Yi, Yuan, Kehua, Ding, Wanbao, and Deng, Lei

Subjects
lncRNA CRNDE, recurrence, SCLM, Cancer Management and Research, lncRNA SNHG7, prognosis, Original Research, synchronous colorectal liver metastasis
Abstract

Peixian Zhang,* Lan Shi,* Linjing Song, Yi Long, Kehua Yuan, Wanbao Ding, Lei Deng Department of Oncology, Yan’an Hospital of Kunming City & Yan’an Hospital Affiliated to Kunming Medical University, Kunming, Yunnan, People’s Republic of China *These authors contributed equally to this workCorrespondence: Lei Deng; Wanbao DingDepartment of Oncology, Yan’an Affiliated Hospital of Kunming Medical University. No. 245 East of Renmin Road, Kunming, Yunnan 650051, People’s Republic of ChinaEmail leidengkm@163.com; wabading@163.comPurpose: Synchronous colorectal liver metastasis (SCLM) had limited availability of tools to predict survival and tumor recurrence. LncRNA CRNDE and lncRNA SNHG7 have been proven to be closely related to cancer progression. However, the predictive value of lncRNA CRNDE and lncRNA SNHG7 in cancer prognosis is still unclear. The purpose of this study was to investigate whether lncRNA CRNDE and lncRNA SNHG7 could be used as promising biomarkers for prognosis prediction of SCLM patients who underwent hepatectomy.Methods: The expression profile of lncRNA CRNDE and lncRNA SNHG7 in serum of SCLM patients was examined by qRT-PCR. The relationship between lncRNA expression and clinicopathological characteristics was analyzed. The Cox proportional-hazards regression model and Kaplan-Meier analysis were performed to analyze the association between lncRNA expression and overall survival (OS) and tumor recurrence of SCLM patients.Results: Levels of lncRNA CRNDE and lncRNA SNHG7 in patients who underwent recurrence or death were significantly higher than that of patients with recurrence-free or survival (P< 0.01). Both lncRNA CRNDE high level and lncRNA SNHG7 high level showed a significant correlation with differentiation of primary tumor, invasion depth of primary focus, lymph node metastases, number of liver metastases, and liver metastasis grade. High levels of lncRNA CRNDE or lncRNA SNHG7 predicted shorter recurrence time, shorter OS time, higher recurrence rate and lower OS rate. Furthermore, lncRNA CRNDE and lncRNA SNHG7 were independent risk factors for high recurrence and poor OS in SCLM underwent hepatectomy.Conclusion: Taken together, lncRNA CRNDE and lncRNA SNHG7 could be promising biomarkers for prediction of OS and tumor recurrence in SCLM underwent hepatectomy.Keywords: lncRNA CRNDE, lncRNA SNHG7, prognosis, recurrence, synchronous colorectal liver metastasis, SCLM

Published
2019

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