Nonparametric motion control in functional connectivity studies in children with autism spectrum disorder [0.03%]
自闭症儿童脑功能连接的非参数运动控制研究
Jialu Ran,Sarah Shultz,Benjamin B Risk et al.
Jialu Ran et al.
Autism spectrum disorder (ASD) is a neurodevelopmental condition associated with difficulties with social interactions, communication, and restricted or repetitive behaviors. To characterize ASD, investigators often use functional connectiv...
Transfer learning estimation of the accelerated failure time model based on high-dimensional data [0.03%]
基于高维数据的加速失效时间模型的迁移学习估计方法研究
Yichen Lou,Mingyue Du,Hui Zhao et al.
Yichen Lou et al.
Motivated by a study on seriously ill hospitalized adults to improve their end-of-life care, we consider estimation of the accelerated failure time model, one of the most commonly used models for regression analysis of failure time data. Al...
Targeted maximum likelihood estimation for mediation analysis with multiple time-varying mediators [0.03%]
具有多个时变中介变量的介导分析的目标最大似然估计
Yan-Lin Chen,Yun-Hao Chang,Sheng-Hsuan Lin
Yan-Lin Chen
Understanding how an exposure influences an outcome through mediators is essential in medical and epidemiological research, especially when mediators vary over time and influence each other reciprocally. This complex condition, termed causa...
Assessing interactive causes of an occurred outcome due to two binary exposures [0.03%]
两种二元暴露下评估已发结果的交互作用原因
Shanshan Luo,Wei Li,Xueli Wang et al.
Shanshan Luo et al.
In contrast to evaluating treatment effects, causal attribution analysis focuses on identifying the key factors responsible for an observed outcome. For two binary exposure variables and a binary outcome variable, researchers need to assess...
Minimum noninferiority dose for phase I clinical trials with immunotherapy [0.03%]
基于免疫疗法的I期临床试验最小非劣效剂量的确立方法研究
Ninghao Zhang,Guosheng Yin
Ninghao Zhang
Recent advancements in immuno-oncology have significantly improved cancer treatments. Compared with traditional clinical trials, the toxicity of these novel therapies is generally low and tolerable, shifting the focus from solely managing t...
Integrative learning of individualized treatment rules from multiple studies with partially overlapping treatments [0.03%]
利用部分重叠治疗的多研究进行个性化治疗方案的综合学习
Yuan Bian,Donglin Zeng,Hyun-Joon Yang et al.
Yuan Bian et al.
An individualized treatment rule (ITR) tailors treatments to a patient's specific characteristics. However, randomized controlled trials (RCTs) are often underpowered to detect the treatment effect heterogeneity needed for reliable ITR esti...
The underlap coefficient as a measure of a biomarker's discriminatory ability [0.03%]
下重叠系数作为一种生物标志物鉴别能力的衡量标准
Zhaoxi Zhang,Vanda Inácio,Miguel de Carvalho
Zhaoxi Zhang
The first step in evaluating a potential diagnostic biomarker is to examine how its values vary across disease stages. In a three-class disease setting, the volume under the receiver operating characteristic surface (VUS) and the three-clas...
A three-groups non-local model for combining heterogeneous data sources to identify genes associated with Parkinson's disease [0.03%]
一种结合异构数据源以识别与帕金森氏症相关的基因的三组非局部模型
Troy P Wixson,Benjamin A Shaby,Daisy L Philtron et al.
Troy P Wixson et al.
We seek to identify genes involved in Parkinson's disease (PD) by combining information across different experiment types. Each experiment, taken individually, may contain too little information to distinguish some important genes from inci...
Dafne Zorzetto,Jenna Landy,Corwin Zigler et al.
Dafne Zorzetto et al.
The impact of wildfire smoke on air quality is a growing concern, contributing to air pollution through a complex mixture of chemical species with important implications for public health. Although previous studies have focused mainly on it...
Decentralized EM algorithm for Gaussian mixtures under data heterogeneity and partial labeling [0.03%]
异质数据下的高斯混合模型的去中心化EM算法及部分标签学习方法研究
Xuetong Li,Shuyuan Wu,Bin Du et al.
Xuetong Li et al.
We systematically study several network-based Expectation-Maximization (EM) algorithms for the Gaussian mixture model within decentralized federated learning (DFL). Our theoretical investigation reveals that directly extending the classic E...