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Your search keyword '"Liang, Baofeng"' showing total 10 results
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10 results on '"Liang, Baofeng"'

4. Comprehensive Assessment Approach for Reservoir Damage Triggered by Fine Particle Deposition

Author

Xing, Yisong, Qin, Zhengshan, Ding, Yangyang, Wenlong, Liu, Chen, Zhihao, He, Yongming, Liang, Baofeng, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Li, Yong, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Oneto, Luca, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zamboni, Walter, Series Editor, Tan, Kay Chen, Series Editor, Chen, Zhe, editor, Yang, Wenming, editor, and Chen, Hao, editor

Published
2024
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5. Effects of High-Velocity Flow on the Temperature Field Near the Wellbore: A Review

Author

Chen, Zhihao, Ding, Yangyang, Qin, Zhengshan, He, Yongming, Liang, Baofeng, Qing, Yalan, Xing, Yisong, Li, Baihong, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Li, Yong, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Oneto, Luca, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zamboni, Walter, Series Editor, Tan, Kay Chen, Series Editor, Chen, Zhe, editor, Yang, Wenming, editor, and Chen, Hao, editor

Published
2024
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10. Predicting treatment failure in stage III colon cancer patients after radical surgery.

Author

Zeng H, Zhong X, Liu W, Liang B, Xue X, Yu N, Xu D, Wang X, and Lin S

Abstract

Purpose: The aim to assess treatment failure in patients with stage III colon cancer who underwent radical surgery and was analyzed using the nomogram., Methods: Clinical factors and survival outcomes for stage III colon cancer patients registered in the SEER database from 2018 to 2019 were analyzed, with patients split into training and testing cohorts (7:3 ratio). A total of 360 patients from the First Affiliated Hospital of Longyan served as an external validation cohort. Independent predictors of treatment failure were identified using logistic regression analyses. The nomograms was evaluated by concordance index (C-index), calibration curves, and the area under the curve (AUC), decision curve analysis (DCA) and clinical impact curves (CIC) assessed the clinical utility of nomograms versus TNM staging., Results: The study included 4,115 patients with stage III colon cancer. Multivariate logistic analysis age, tumor site, pT stage, pN stage, chemotherapy, pretreatment CEA levels, number of harvested lymph nodes, perineural invasion and marital status were identified as independent risk factors for treatment failure. The C-indices for the training and testing sets were 0.853 and 0.841. Validation by ROC and calibration curves confirmed the stability and reliability of the model. DCA showed that the net clinical effect of the histogram was superior to that of the TNM staging system, while CIC highlighted the potentially large clinical impact of the model., Conclusions: The developed Nomogram provides a powerful and accurate tool for clinicians to assess the risk of treatment failure after radical surgery in patients with stage III colon cancer., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Zeng, Zhong, Liu, Liang, Xue, Yu, Xu, Wang and Lin.)

Published
2024
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