Zobrazeno 1 - 10
of 350
pro vyhledávání: '"Li, Kexuan"'
Lung adenocarcinoma (LUAD) is characterized by substantial genetic heterogeneity, posing challenges in identifying reliable biomarkers for improved diagnosis and treatment. Tumor Mutational Burden (TMB) has traditionally been regarded as a predictive
Externí odkaz:
http://arxiv.org/abs/2411.01773
Autor:
Hu, Chen, Huang, Yian, Li, Kexuan, Zhang, Luping, Zhu, Yiming, Peng, Yufei, Pu, Tian, Peng, Zhenming
Infrared small target detection (IRSTD) is widely used in civilian and military applications. However, IRSTD encounters several challenges, including the tendency for small and dim targets to be obscured by complex backgrounds. To address this issue,
Externí odkaz:
http://arxiv.org/abs/2409.19599
Autor:
Li, Kexuan
Genome-Wide Association Studies (GWAS) face unique challenges in the era of big genomics data, particularly when dealing with ultra-high-dimensional datasets where the number of genetic features significantly exceeds the available samples. This paper
Externí odkaz:
http://arxiv.org/abs/2312.15055
This article studies the derivatives in models that flexibly characterize the relationship between a response variable and multiple predictors, with goals of providing both accurate estimation and inference procedures for hypothesis testing. In the s
Externí odkaz:
http://arxiv.org/abs/2308.13905
Clinical trials often involve the assessment of multiple endpoints to comprehensively evaluate the efficacy and safety of interventions. In the work, we consider a global nonparametric testing procedure based on multivariate rank for the analysis of
Externí odkaz:
http://arxiv.org/abs/2306.15380
A bioequivalence study is a type of clinical trial designed to compare the biological equivalence of two different formulations of a drug. Such studies are typically conducted in controlled clinical settings with human subjects, who are randomly assi
Externí odkaz:
http://arxiv.org/abs/2306.06698
In this work, we propose a deep learning-based method to perform semiparametric regression analysis for spatially dependent data. To be specific, we use a sparsely connected deep neural network with rectified linear unit (ReLU) activation function to
Externí odkaz:
http://arxiv.org/abs/2301.03747
Autor:
Li, Kexuan
Variable selection problem for the nonlinear Cox regression model is considered. In survival analysis, one main objective is to identify the covariates that are associated with the risk of experiencing the event of interest. The Cox proportional haza
Externí odkaz:
http://arxiv.org/abs/2211.09287
The applications of traditional statistical feature selection methods to high-dimension, low sample-size data often struggle and encounter challenging problems, such as overfitting, curse of dimensionality, computational infeasibility, and strong mod
Externí odkaz:
http://arxiv.org/abs/2204.01682
Publikováno v:
In Engineering Structures 15 September 2024 315
