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Development and validation of a nomogram prediction model for overall survival in patients with rectal cancer

World Journal of Gastrointestinal Oncology 2025年第2期17卷 93-104页

作者： Ling Liang Xiao-Sheng Li Ze-Jun Huang Zu-Hai Hu Qian-Jie Xu Yu-Liang Yuan Wei Zhang Hai-Ke Lei Chongqing Key Laboratory of Translational Research for Cancer Metastasis and Individualized Treatment Chongqing University Cancer HospitalChongqing 400030China Chongqing Cancer Multiomics Big Data Application Engineering Research Center Chongqing University Cancer HospitalChongqing 400030China Department of Health Statistics School of Public HealthChongqing Medical UniversityChongqing 400016China

BACKGROUND Rectal cancer is prevalent and associated with substantial morbidity and *** To develop a nomogram prediction model for overall survival(OS)in patients with rectal cancer by leveraging a comprehensive analysis of demographic,clinicopathological,haematological,and follow-up data to identify independent prognostic *** We conducted a prospective cohort study in China involving rectal cancer patients and applied Cox regression and least absolute shrinkage and selection operator regression to assess the significance of various variables as independent prognostic factors for *** identified factors were integrated into a nomogram model,which was evaluated for predictive accuracy via the C-index,area under the curve(AUC),calibration curve,and decision curve analysis(DCA).RESULTS Multivariate analysis revealed independent predictors of OS,including the Karnofsky performance status,age,sex,TNM stage,chemotherapy,surgery,targeted therapy,β2-microglobulin,lactate dehydrogenase,and the neutrophil-to-lymphocyte *** nomogram demonstrated a C-index of 0.80 for the training and validation cohorts,with AUC values indicating high predictive accuracy for 1-year,3-year,and 5-year *** calibration curves confirmed the model's excellent agreement with the observed survival rates,and DCA revealed the superior clinical utility of the nomogram over the TNM staging *** In this study,a novel prognostic model that accurately predicts the OS of rectal cancer patients was *** model exhibited excellent discriminatory and calibration capabilities,thus offering a reliable tool for health care professionals to estimate patient survival.

关键词： Rectal cancer Overall survival Nomogram Prognosis

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Development and validation of a nomogram model for predicting overall survival in patients with gastric carcinoma

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World Journal of Gastrointestinal Oncology 2025年第2期17卷 132-143页

作者： Guan-Zhong Liang Xiao-Sheng Li Zu-Hai Hu Qian-Jie Xu Fang Wu Xiang-Lin Wu Hai-Ke Lei Chongqing Key Laboratory of Translational Research for Cancer Metastasis and Individualized Treatment Chongqing University Cancer HospitalChongqing 400030China Chongqing Cancer Multi-omics Big Data Application Engineering Research Center Chongqing University Cancer HospitalChongqing 400030China Department of Health Statistics School of Public HealthChongqing Medical UniversityChongqing 400016China Research Center for Medicine and Social Development School of Public HealthChongqing Medical UniversityChongqing 400016China The Research Center of Big Data Chongqing University Cancer HospitalChongqing 400030China

BACKGROUND The prevalence and mortality rates of gastric carcinoma are disproportionately elevated in China,with the disease's intricate and varied characteristics further amplifying its health *** forecasting of overall survival(OS)is of paramount importance for the clinical management of individuals afflicted with this *** To develop and validate a nomogram model that provides precise gastric cancer prevention and treatment guidance and more accurate survival outcome prediction for patients with gastric *** data analysis was conducted on samples collected from hospitalized gastric cancer patients between 2018 and *** absolute shrinkage and selection operator,univariate,and multivariate Cox regression analyses were employed to identify independent prognostic factors.A nomogram model was developed to predict gastric cancer patient *** model's predictability and discriminative ability were evaluated via receiver operating characteristic *** evaluate the clinical utility of the model,Kaplan-Meier and decision curve analyses were *** A total of ten independent prognostic factors were identified,including body mass index,tumor-node-metastasis(TNM)stage,radiation,chemotherapy,surgery,albumin,globulin,neutrophil count,lactate dehydrogenase,and platelet-to-lymphocyte *** area under the curve(AUC)values for the 1-,3-,and 5-year survival prediction in the training set were 0.843,0.850,and 0.821,*** AUC values were 0.864,0.820,and 0.786 for the 1-,3-,and 5-year survival prediction in the validation set,*** model exhibited strong discriminative ability,with both the time AUC and time C-index exceeding *** with TNM staging,the model demonstrated superior clinical ***,a nomogram was developed via a web-based *** This study established and validated a novel nomogram model for predicting the OS of gastric cancer patients,which demonstrat

关键词： Gastric carcinoma Prediction Overall survival Nomogram Prospective

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Functional Bayesian Additive Regression Trees with Shape Constraints

arXiv

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arXiv 2025年

作者： Cao, Jiahao He, Shiyuan Zhang, Bohai Institute of Statistics and Big Data Renmin University of China Beijing100872 China School of Mathematics and Statistics Beijing Technology and Business University Beijing100048 China Guangdong Provincial Key Laboratory of Interdisciplinary Research and Application for Data Science BNU-HKBU United International College Zhuhai519087 China

Motivated by the great success of Bayesian additive regression trees (BART) on regression, we propose a nonparametric Bayesian approach for the function-on-scalar regression problem, termed as Functional BART (FBART). Utilizing spline-based function representation and tree-based domain partition model, FBART offers great flexibility in characterizing the complex and heterogeneous relationship between the response curve and scalar covariates. We devise a tailored Bayesian backfitting algorithm for estimating the parameters in the FBART model. Furthermore, we introduce an FBART model with shape constraints on the response curve, enhancing estimation and prediction performance when prior shape information of response curves is available. By incorporating a shape-constrained prior, we ensure that the posterior samples of the response curve satisfy the required shape constraints (e.g., monotonicity and/or convexity). Our proposed FBART model and its shape-constrained version are the new advances of BART models for functional data. Under certain regularity conditions, we derive the posterior convergence results for both FBART and its shape-constrained version. Finally, the superiority of the proposed methods over other competitive counterparts is validated through simulation experiments under various settings and analyses of two real datasets. Copyright © 2025, The Authors. All rights reserved.

关键词： Trees (mathematics)

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Oesophageal cancer-specific mortality risk and public health insurance: Prospective cohort study from China

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World Journal of Gastrointestinal Oncology 2025年第4期17卷 274-285页

作者： Xiang-Lin Wu Xiao-Sheng Li Jing-Han Cheng Lin-Xin Deng Zu-Hai Hu Jun Qi Hai-Ke Lei Chongqing Key Laboratory of Translational Research for Cancer Metastasis and Individualized Treatment Chongqing University Cancer HospitalChongqing 400030China Chongqing Cancer Multi-omics Big Data Application Engineering Research Center Chongqing University Cancer HospitalChongqing 400030China Research Center for Medicine and Social Development Chongqing Medical UniversityChongqing 400016China Department of Health Statistics School of Public HealthChongqing Medical UniversityChongqing 400016China Department of Thoracic Surgery The People’s Hospital of Changshou ChongqingChongqing 401220China

BACKGROUND Oesophageal cancer is a significant health concern worldwide,with high inci-dence and mortality *** China,the disease burden is particularly high,accounting for a substantial proportion of oesophageal cancer cases and related deaths *** To explore the relationship between the mortality rate of oesophageal cancer patients and insurance type,out-of-pocket ratio,and the joint effects of insurance type and out-of-pocket *** The χ^(2) test was used to analyze patients’demographic and clinical *** logistic regression,the Cox proportional hazard model,and the competitive risk model were used to calculate the cumulative hazard ratios(HRs)of all-cause death and oesophageal cancer-specific death among patients with different types of insurance and out-of-pocket *** Compared with patients covered by basic medical insurance for urban and rural residents,patients covered by urban employee basic medical insurance for urban workers(UEBMI)had a 23.30%increased risk of oesophageal cancer-specific death[HR=1.233,95%confidence interval(CI):1.093-1.391,P<0.005].Compared with patients in the low out-of-pocket ratio group,patients in the high out-of-pocket ratio group had a 25.80%reduction in the risk of oesophageal cancer-specific death(HR=0.742,95%CI:0.6555-0.84,P<0.005).With each 10%increase in the out-of-pocket ratio,the risk of oesophageal cancer-specific death decreased by 10.10%in patients covered by ***,the risk of oesophageal cancer-specific death increased by 26.90%in patients in the high out-of-pocket ratio *** This study reveals the relationships of the specific mortality rate of patients with oesophageal cancer with the out-of-pocket ratio and medical insurance types as well as their combined *** study provides practical suggestions and guidance for the formulation of relevant policies in this area.

关键词： Oesophageal cancer Public health Insurance Prognosis Mortality risk

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Semi-Supervised Feature Selection With Multi-Scale Fuzzy Information Fusion: From Both Global and Local Perspectives

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IEEE Transactions on Fuzzy Systems 2025年

作者： Zhou, Nan Liao, Shujiao Chen, Hongmei Ding, Weiping Lu, Yaqian Minnan Normal University School of Mathematics and Statistics Fujian Key Laboratory of Granular Computing and Applications Zhangzhou363000 China Southwest Jiaotong University School of Computing and Artificial Intelligence National Engineering Laboratory of Integrated Transportation Big Data Application Technology Chengdu611756 China Nantong University School of Artificial Intelligence and Computer Science Nantong226019 China City University of Macau Faculty of Data Science 999078 China

In reality, the laborious nature of label annotation leads to the widespread existence of limited labeled data. Moreover, multi-scale data have received widespread attention due to its rich knowledge representation. However, current research on multi-scale data primarily focuses on supervised learning environments, while semi-supervised feature selection for multi-scale data with limited labels remains inadequately explored. Meanwhile, existing studies on multi-scale data often emphasize selecting optimal scales and further conducting feature selection, but this strategy may result in losing potentially valuable information from other scales. To overcome these limitations, by adopting a multi-scale fuzzy information fusion mechanism, this article proposes two new semi-supervised feature selection approaches for multi-scale data with limited labels from both global and local perspectives. Initially, by fusing fuzzy information at various scales, a label learning method is proposed to convert the decision of missing labels into a fuzzy decision of label distribution. Subsequently, label-distributed multi-scale fuzzy global and local rough sets are constructed from global and local perspectives, respectively. Based on the two models, two semi-supervised feature selection algorithms are developed based on global and local multi-scale fuzzy information fusion. Experimental results demonstrate that, compared to other advanced feature selection algorithms, the two proposed algorithms can effectively handle multi-scale data with limited labels and exhibit superior classification performance, computational efficiency and robustness. © 1993-2012 IEEE.

关键词： Self-supervised learning

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Theoretical analysis of the convergence property of a basic pigeon-inspired optimizer in a continuous search space

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Science China(Information Sciences) 2019年第7期62卷 90-98页

作者： Yushan ZHANG Han HUANG Hongyue WU Zhifeng HAO School of Statistics and Mathematics Guangdong University of Finance and Economics Big Data and Educational Statistics Application Laboratory Guangdong University of Finance and Economics School of Software Engineering South China University of Technology School of Mathematics and Big Data Foshan University

The pigeon-inspired optimization(PIO) algorithm is a newly presented swarm intelligence optimization algorithm inspired by the homing behavior of pigeons. Although PIO has demonstrated effectiveness and superiority in numerous fields, particularly in practical engineering optimization, there have been few results concerning the theoretical foundations of PIO. This paper conducts convergence analysis of basic PIO in a continuous search space in two aspects. First, we analyze the convergence of each pigeon's expected position using a difference equation and prove that the average position of each pigeon in the swarm will converge to the same value. To further study the stochastic global convergence property of the pigeon swarm, we apply the martingale theory to investigate the basic PIO swarm sequence, and achieve a sufficient condition to guarantee global convergence of the basic PIO. Our theoretical analysis shows that this convergence depends upon the accumulation of the minimum probability with which the pigeon swarm jumps to the global-optimal region at each iteration. The mathematical methods proposed in this study, particularly the martingale technique, also provide a new effective approach for the theoretical analysis of bio-inspired algorithms in continuous optimization.

关键词： pigeon-inspired optimization(PIO) convergence analysis martingale continuous optimization swarm intelligence

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On Boolean elements and derivations in 2-dimension linguistic lattice implication algebras

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Applied Mathematics(A Journal of Chinese Universities) 2023年第2期38卷 274-292页

作者： ZHU Hua ZHAO Jian-bin School of Mathematics and Statistics Zhengzhou UniversityZhengzhou 450001China Henan Academy of Big Data Zhengzhou UniversityZhengzhou 450001China Henan Key Laboratory of Financial Engineering Zhengzhou 450001China Key Laboratory of Big Data Analysis and Application Zhengzhou 450001China

A 2-dimension linguistic lattice implication algebra(2DL-LIA)can build a bridge between logical algebra and 2-dimension fuzzy linguistic *** this paper,the notion of a Boolean element is proposed in a 2DL-LIA and some properties of Boolean elements are *** derivations on 2DL-LIAs are introduced and the related properties of derivations are ***,it proves that the derivations on 2DL-LIAs can be constructed by Boolean elements.

关键词： derivation Boolean element Lattice implication algebra(LIA) 2-dimension linguistic lattice implication algebra(2DL-LIA) 2-dimension fuzzy linguistic information

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Improvement design of agricultural plant protection UAV

Improvement design of agricultural plant protection UAV

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2020 International Conference on Artificial Intelligence and Electromechanical Automation, AIEA 2020

作者： Wang, Xi Gu, Yongyi Ye, Chuanyuan Academy of Art and Design Guangdong Agriculture Industry Business Polytechnic Guangzhou China Big Data and Educational Statistics Application Laboratory Guangdong University of Finance and Economics Guangzhou China

ISBN: (纸本)9781728182889

This paper mainly introduces the definition, classification and structure of agricultural plant protection UAV, analyzes the main problems existing in the current design of agricultural plant protection UAV, puts forward the improved design practice scheme, and enriches the product categories of domestic plant protection UAV. © 2020 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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Mutable hierarchy feature selection based on generalized fuzzy rough sets

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Applied Soft Computing 2025年 177卷

作者： Zilong Lin Yaojin Lin Chenxi Wang Jinkun Chen School of Computer Science Minnan Normal University Zhangzhou 363000 PR China Key Laboratory of Data Science and Intelligence Application Minnan Normal University Zhangzhou Fujian 363000 PR China Fujian Key Laboratory of Big Data Application and Intellectualization for Tea Industry Wuyi University Wuyishan Fujian 354300 PR China School of Mathematics and Statistics Minnan Normal University Zhangzhou Fujian 363000 PR China

Hierarchical classification divides data into correlated sub-tasks from coarse to fine. Compared to flat classification, it is more complex and suffers from the curse of dimensionality. Existing hierarchical Fuzzy Rough Sets (FRS) methods only stay at the fine-grained to select the features, which is a fine-grained search strategy. Thus, we propose a coarse-grained search strategy and use Generalized Fuzzy Rough Sets (GFRS) to enhance its robustness. Furthermore, we introduce the concept of tree fragmentation. Though assessing the degree of fragmentation in the tree structure, it selects an appropriate granularity search strategy for hierarchical tree-structured datasets. Finally, we combine both granularity search strategies and collectively named - Mutable Hierarchy Search Strategy (MHSS); the entire proposed algorithm is named - Mutable Hierarchy Feature Selection Based on Generalized Fuzzy Rough Sets (MHFS). We compare two FRS-based feature selection algorithms, three hierarchical optimization methods, and six flat feature selection methods. Extensive experiments demonstrate the performance of our method.

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The Influence of Enterprise Financing Structure in China on Business Performance—Simulation Analysis Based on the System Dynamics 12th

The Influence of Enterprise Financing Structure in China on ...

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12th EAI International Conference on Simulation Tools and Techniques, SIMUtools 2020

作者： Li, Chenggang Wan, Jun College of Big Data Application and Economics Guizhou University of Finance and Economics Guiyang550025 China Guizhou Key Laboratory of Big Data Statistics Analysis Guizhou University of Finance and Economics Guiyang Guizhou China

ISBN: (纸本)9783030727949

Enterprise financing structure has an impact on the profitability and solvency of the enterprise to some extent, which is also called the influence on business performance. Enterprise managers and scholars have always focused on the influence of enterprise financing structure on business performance. This paper selects the data of the listed companies from 2010 to 2018, uses the method of the system dynamics, constructs the system dynamics model of enterprise financing structure, and simulates and analyzes the influence of equity financing and debt financing on enterprise business performance. The simulation shows: (1) Equity financing has an active impact on the rate of total assets and scale, while a negative impact on asset liability ratio. (2) Debt financing has an active impact on the rate of total assets, liability assets and scale. (3) Between the two external financing, the influence of equity financing on the business performance is better than the debt financing’s. © ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2021.

关键词： Commerce

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