A HORSESHOE MIXTURE MODEL FOR BAYESIAN SCREENING WITH AN APPLICATION TO LIGHT SHEET FLUORESCENCE MICROSCOPY IN BRAIN IMAGING [0.03%]
一种贝叶斯筛选的马蹄形混合模型及其在大脑成像光片荧光显微镜中的应用
Francesco Denti,Ricardo Azevedo,Chelsie Lo et al.
Francesco Denti et al.
In this paper we focus on identifying differentially activated brain regions using a light sheet fluorescence microscopy-a recently developed technique for whole-brain imaging. Most existing statistical methods solve this problem by partiti...
DATA-ADAPTIVE EFFICIENT ESTIMATION STRATEGIES FOR BIOMARKER STUDIES EMBEDDED IN RANDOMIZED TRIALS [0.03%]
基于随机试验中嵌入的生物标志物研究的数据自适应高效估计策略
Wei Zhang,Zhiwei Zhang,James F Troendle et al.
Wei Zhang et al.
Predictive and prognostic biomarkers are increasingly important in clinical research and practice. Biomarker studies are frequently embedded in randomized clinical trials with biospecimens collected at baseline and assayed for biomarkers, e...
JOINT IDENTIFICATION OF SPATIALLY VARIABLE GENES VIA A NETWORK-ASSISTED BAYESIAN REGULARIZATION APPROACH [0.03%]
基于网络辅助贝叶斯正则化的可变空间基因联合识别方法
Mingcong Wu,Yang Li,Shuangge Ma et al.
Mingcong Wu et al.
Identifying genes that display spatial patterns is critical to investigating expression interactions within a spatial context and further dissecting biological understanding of complex mechanistic functionality. Despite the increase in stat...
TEMPORAL MODELS FOR ESTIMATION AND SHORT-TERM FORECASTING OF NEONATAL MORTALITY RATES IN SUB-SAHARAN AFRICA [0.03%]
非洲撒哈拉以南地区估计和短期预测新生儿死亡率的时空模型
Katherine R Paulson,Geir-Arne Fuglstad,Zehang Richard Li et al.
Katherine R Paulson et al.
Accurate estimation and forecasts for neonatal mortality rates (NMRs) in low- and middle-income countries is an urgent problem. Much of child mortality is preventable, and understanding temporal trends is of great interest when evaluating p...
Small Area Estimation of Education Levels in Low- and Middle-Income Countries [0.03%]
发展中低收入国家的小区域教育水平估计
Yunhan Wu,Ameer Dharamshi,Jon Wakefield
Yunhan Wu
Education is a key driver of social and economic mobility, yet disparities in attainment persist, particularly in low- and middle-income countries (LMICs). Existing indicators, such as mean years of schooling for adults aged 25 and older (M...
BIOMARKER DETECTION FOR DISEASE CLASSIFICATION IN LONGITUDINAL MICROBIOME DATA [0.03%]
纵向微生物组数据中的疾病分类生物标志物检测
Chao Cheng,Hanteng Ma,Yujie Zhong et al.
Chao Cheng et al.
The microbiome has been found to have a close relationship with human health. Advancements in sequencing technologies have enabled in-depth studies of microbial communities and their associations with various diseases. When analyzing microb...
A general framework for investigating neurodevelopment of brain functional networks using multisite and longitudinal neuroimaging [0.03%]
一种利用多模态和纵向神经影像数据探究大脑功能网络神经发育的通用框架
Joshua Lukemire,Yaotian Wang,Ying Guo
Joshua Lukemire
In recent years longitudinal, multi-site imaging studies have emerged as key tools for investigating brain function. These studies follow a large number of participants for an extended period, offering exciting opportunities to uncover brai...
DYNAMIC CLASSIFICATION OF LATENT DISEASE PROGRESSION WITH AUXILIARY SURROGATE LABELS [0.03%]
基于辅助替代标签的潜在疾病进展动态分类方法
Zexi Cai,Donglin Zeng,Karen S Marder et al.
Zexi Cai et al.
Disease progression prediction based on patients' evolving health information is challenging when true disease states are unknown due to diagnostic capabilities or high costs. For example, the absence of gold-standard neurological diagnoses...
SEMIPARAMETRIC ANALYSIS OF INTERVAL-CENSORED DATA SUBJECT TO INACCURATE DIAGNOSES WITH A TERMINAL EVENT [0.03%]
具有误诊和终事件的区间删失数据的半参数分析方法研究
Yuhao Deng,Donglin Zeng,Yuanjia Wang
Yuhao Deng
Interval-censoring frequently occurs in studies of chronic diseases where disease status is inferred from intermittently collected biomarkers. Although many methods have been developed to analyze such data, they typically assume perfect dis...
A BAYESIAN GROWTH MIXTURE MODEL FOR COMPLEX SURVEY DATA: CLUSTERING POSTDISASTER PTSD TRAJECTORIES [0.03%]
复杂调查数据的贝叶斯成长混合模型：分类灾害后的创伤应激群集心理轨迹
Rebecca Anthopolos,Qixuan Chen,Joseph Sedransk et al.
Rebecca Anthopolos et al.
Research on growth mixture models (GMMs) for analyzing data from a complex sample survey is sparse. Existing methods use pseudo-likelihood in which survey weights are incorporated into the likelihood function, with variance estimated via li...