Zobrazeno 1 - 10
of 350
pro vyhledávání: '"LI Kexuan"'
Autor:
LI Kexuan, SUN Zhen, QIU Huizhong, WU Bin, LIN Guole, LU Junyang, SUN Xiyu, NIU Beizhan, XU Lai, XIAO Yi
Publikováno v:
Xiehe Yixue Zazhi, Vol 14, Iss 3, Pp 566-574 (2023)
Objective By collecting the patient information in the Colon Cancer Database of Peking Union Medical College Hospital since its establishment, we aim to demonstrate the completeness of the clinicopathological characteristics and follow-up data to pro
Externí odkaz:
https://doaj.org/article/dcd5a8de37af467a8ecd5695a3b10273
Publikováno v:
MATEC Web of Conferences, Vol 401, p 03004 (2024)
The content of C element and in-situ Ti2AlC phase is adjusted to reduce the content of B2 phase in the TiAl matrix, ultimately improving the compressive properties of TiAl alloys. Results show that there is a high content of B2 phase inside the lamel
Externí odkaz:
https://doaj.org/article/25177a36e1c642bda5641e8883897674
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