A5045361404- Complex Network Analysis Techniques
- Advanced Graph Neural Networks
- Advanced Statistical Methods and Models
- Statistical Methods and Inference
- Anomaly Detection Techniques and Applications
- Bayesian Methods and Mixture Models
- Renal and related cancers
- Fault Detection and Control Systems
- Bioinformatics and Genomic Networks
- Advanced Clustering Algorithms Research
- Epigenetics and DNA Methylation
- Renal cell carcinoma treatment
- Statistical Methods and Bayesian Inference
- Technology and Data Analysis
- Data Stream Mining Techniques
- Energy Load and Power Forecasting
- Cholangiocarcinoma and Gallbladder Cancer Studies
- Wind Energy Research and Development
- Astronomical Observations and Instrumentation
- Statistical Distribution Estimation and Applications
- Biliary and Gastrointestinal Fistulas
- Single-cell and spatial transcriptomics
- Advanced Computing and Algorithms
- Machine Learning in Healthcare
- Immune Cell Function and Interaction
Chaozhou Central Hospital
2024
Lanzhou University
2021-2024
First Affiliated Hospital of GuangXi Medical University
2022-2024
Guangxi Medical University
2022-2024
Lanzhou University of Finance and Economics
2014-2023
Shanghai University
2012
We report the isolation of Helicobacter cholecystus from a positive blood culture 58-year-old male with bacteremia and acute cholecystitis, in China. The patient's condition improved after symptomatic support treatment subtotal cholecystectomy. This suggests that H. should be considered potential human pathogen.
The objective of this paper is to propose an efficient regression algorithm survival analysis - SurvivalBoost.. This based on Random Survival Forests (RSF) and XGBoost. By combining the Elastic-Net penalty type Cox proportional hazards model with XGBoost optimal algorithm, our more suitable for analysis. performance proposed compared model, XGBoost, CoxBoost, RSF Gradient Boosting Desicion Tree-based 4 simulated datasets real datasets. results illustrated superiority algorithm.
Nephroblastoma, also known as Wilms' tumor (WT), remains one of the major causes tumor-related deaths worldwide in children. Cancer stem cells (CSCs) are considered to be main culprits cancer resistance and disease recurrence, which reported multiple types tumors. However, research on CSCs WT is limited. Therefore, our study aimed identify key genes related provide new ideas for treating WT.The RNA-seq clinical data samples were obtained from University California Santa Cruz (UCSC) Xena...
Variable selection is an effective methodology for dealing with models numerous covariates. We consider the methods of variable semiparametric Cox proportional hazards model under progressive Type-II censoring scheme. The used to influence coefficients environmental By applying Breslow’s “least information” idea, we obtain a profile likelihood function estimate coefficients. Lasso-type penalized estimation as well stepwise method are explored means find important Numerical simulations...
Machine learning methods have been extensively used in survival analysis. SurvivalBoost - a machine-learning-based regression algorithm, focused on Elastic-net-Type penalized semiparametric Cox model XGBoost and random forests, has verified its superior prediction performance real simulated datasets. Whereas the interpretability is remain undiscovered. This paper discusses of this algorithm upon using Shapley Additive Explanation (SHAP) value. It illustrated that can be more effective to...
Communication is one of the most important steps in constructing a robotic system. Such system has been built based on NI LabVIEW and compactRIO. In this paper, several methods communication between host computer compactRIO were introduced. By comparison experiment, we found that each method their unique benefits drawbacks. The shared variables convenient; TCP/IP reliable; UDP highest performance. When set up, suitable them should be selected according to user's requirement.
<title>Abstract</title> The appearance of outliers results in a complexity to achieve an accurate classify. This paper aims the detection and identification outlier before selecting suitable classifier. problem is firstly converted high-dimensional regression, then we propose novel method on combination multiple-correlation-coefficientbased feature selection for dimensional reduction, t−test sparsification, iterated algorithm also given. Performance simulated numerical data applications...
Background Diffuse large B-cell lymphoma (DLBCL) represents the most prevalent form of aggressive non-Hodgkin lymphoma. Despite receiving standard treatment, a subset patients undergoes refractory or recurrent cases, wherein involvement cancer stem cells (CSCs) could be significant. Methods We comprehensively characterized B cell subpopulations using single-cell RNA sequencing data from three DLBCL samples and one normal lymph tissue. The CopyKat R package was employed to assess malignancy...
The clustering on categorical variables has received intensive attention. In dataset with features, some features show the superior performance procedure. this paper, we propose a simple method to find such distinctive by comparing pooled within-cluster mean relative difference and then partition data upon give subspace of subgroups. applications zoo soybean illustrate proposed method.
Identifying communities is an important problem in network analysis.Various approaches have been proposed the literature, but most of them either rely on topological structure or node attributes, with few integrating both aspects.Here we propose a community detection approach based spectral clustering combining information and attributes (SpcSA).Some may not describe are trying to detect correctly.These irrelevant can add noise lower overall accuracy detection.To determine how much each...
Community detection is an effective exploration technique for analyzing networks. Most of the network data not only describes connections nodes but also properties nodes. In this paper, we propose a community method collects relevant evidences from information node attributes and structure to assist task on node-attributed We find communities in framework semidefinite programming (SDP) method. practical applications, distribution some may be uncorrelated with or itself contain no as random...
A multilayer network is a useful representation for real-world complex systems in which multiple types of connections are formed between entities. Connections the same type form specific layer network. We propose novel framework predicting links target by taking into account interlayer structural information. The method depends on intuitive assumption that two node pairs tend to have similar connection patterns if these nodes similar. Further, prediction accuracy will be improved information...
Data stream mining has recently been studied extensively in the literature. Many clustering algorithms were proposed to handle massive streams of data. However, many these may not be as efficient one desires for data streams, they typically require a number iterations their implementations. In this paper, we will propose new algorithm, based on fast density-peak-search method. It does any its implementation, and therefore is most suitable large The comparisons numerical illustration well...