Multilevel Multivariate Functional Principal Component Analysis of Evoked and Induced Event-Related Spectral Perturbations [0.03%]
多水平多元功能主成分分析在诱发和诱导事件相关光谱评估中的应用
Mingfei Dong,Donatello Telesca,Abigail Dickinson et al.
Mingfei Dong et al.
Event-related spectral perturbations (ERSPs) capture dynamic changes in electroencephalography (EEG) power across frequency and trial time. Even though they are obtained at the trial level, they are commonly averaged across trials and analy...
Robust Privacy-Preserving Models for Cluster-Level Confounding: Recognizing Disparities in Access to Transplantation [0.03%]
鲁棒的隐私保护模型用于群组级混杂因素：识别移植准入的差异性
Nicholas Hartman,Kevin He
Nicholas Hartman
In health services applications where the patients are clustered within common institutions or geographic regions, it is often of interest to estimate the treatment effects of the medical providers after adjusting for confounding risk facto...
Central Posterior Envelopes for Bayesian Longitudinal Functional Principal Component Analysis [0.03%]
基于贝叶斯纵向函数主成分分析的中心后包层
Joanna Boland,Qi Qian,Donatello Telesca et al.
Joanna Boland et al.
Longitudinally observed functional data are commonly encountered in biomedical studies. Under the weak separability assumption of the high dimensional covariance, the recently proposed Bayesian longitudinal functional principal component an...
Joint Modeling of Geometric Features of Longitudinal Process and Discrete Survival Time Measured on Nested Timescales: An Application to Fecundity Studies [0.03%]
基于嵌套时间尺度的纵向过程几何特征与离散生存时间的联合建模及其在生育力研究中的应用
Abhisek Saha,Ling Ma,Animikh Biswas et al.
Abhisek Saha et al.
In biomedical studies, longitudinal processes are collected till time-to-event, sometimes on nested timescales (example, days within months). Most of the literature in joint modeling of longitudinal and time-to-event data has focused on mod...
Weighted Brier Score - an Overall Summary Measure for Risk Prediction Models with Clinical Utility Consideration [0.03%]
具有临床实用性的风险预测模型的总体综合评估指标：加权Brier分数
Kehao Zhu,Yingye Zheng,Kwun Chuen Gary Chan
Kehao Zhu
As advancements in novel biomarker-based algorithms and models accelerate their use in disease risk prediction, it is crucial to evaluate these models within the context of their intended clinical application. Prediction models output the a...
Advancing Statistical Approaches for Modeling Exposure Mixtures and Health Outcomes [0.03%]
用于表征暴露混合物和健康结局的统计方法的发展
Zhen Chen,Paul S Albert
Zhen Chen
A Variance-Based Sensitivity Analysis Approach for Identifying Interactive Exposures [0.03%]
一种基于方差分析法的交互作用识别方法以发现敏感暴露因素
Ruijin Lu,Boya Zhang,Anna Birukov et al.
Ruijin Lu et al.
Chemical mixtures can significantly affect human health, but understanding the interactions among various chemical exposures and identifying influential ones in relation to some health outcomes are difficult. Bayesian kernel machine regress...
Novel Scalar-on-matrix Regression for Unbalanced Feature Matrices [0.03%]
新颖的标量对矩阵回归方法及其在不平衡特征矩阵上的应用研究
Jeremy Rubin,Fan Fan,Laura Barisoni et al.
Jeremy Rubin et al.
Image features that characterize tubules from digitized kidney biopsies may offer insight into disease prognosis as novel biomarkers. For each subject, we can construct a matrix whose entries are a common set of image features (e.g., area, ...
Intergenerational Associations Between Maternal Diet and Childhood Adiposity: A Bayesian Regularized Mediation Analysis [0.03%]
基于贝叶斯正则化的介导分析评估母亲饮食与儿童肥胖的代际关联
Yu-Bo Wang,Cuilin Zhang,Zhen Chen
Yu-Bo Wang
Growing evidence supports a positive association between childhood obesity and chronic diseases in later life. It is also suggested that childhood obesity is more prevalent for children born from pregnancies complicated by metabolic disorde...
Enhancing Genetic Risk Prediction through Federated Semi-Supervised Transfer Learning with Inaccurate Electronic Health Record Data [0.03%]
基于不准确电子健康记录数据的联邦半监督迁移学习遗传风险预测方法
Yuying Lu,Tian Gu,Rui Duan
Yuying Lu
Large-scale genomics data combined with Electronic Health Records (EHRs) illuminate the path towards personalized disease management and enhanced medical interventions. However, the absence of "gold standard" disease labels makes the develo...