Innovative statistical method for longitudinal and hierarchical data modeling: the GMEXGBoost method [0.03%]
一种纵向和层级数据建模的创新统计方法：GMEXGBoost算法
Fariba Asadi,Reza Homayounfar,Yaser Mehrali et al.
Fariba Asadi et al.
Introduction and objectives: Over recent decades, the exponential growth of data, especially in healthcare, has necessitated advanced analytical methods. Conventional machine learning algorithms often assume independence ...
Cluster minimal sufficient balance (CMSB): an efficient covariate balancing randomization method for cluster randomized trials [0.03%]
群体最小充分平衡(CMSB)：群组随机试验中一种有效的协变量平衡随机化方法
Jiaxin Cai,Shanshan Suo,Valirie Ndip et al.
Jiaxin Cai et al.
Background: Cluster randomized trials (CRTs) require balanced baseline covariates to yield unbiased estimates of treatment effects. Existing approaches such as constrained randomization can improve balance but may comprom...
Consistency of primary outcomes in evidence synthesis researches on drug-eluting stents for coronary artery disease [0.03%]
药物洗脱支架治疗冠心病证据综合研究主要结局指标的一致性分析
Xiaoqing Lin,Songsong Tan,Yuezi Huang et al.
Xiaoqing Lin et al.
Background: As the number of systematic reviews (SRs) and meta-analyses (MAs) evaluating drug-eluting stents (DES) for coronary artery disease (CAD) continues to grow, the need for standardized primary outcomes has become...
An 11-Year (2012-2022) review of Journal of Athletic Training publication study designs and sample sizes [0.03%]
《运动医学杂志》（2012-2022年）研究设计和样本量的回顾性分析
Zachary K Winkelmann,Samantha E Scarneo-Miller,Emily C Smith et al.
Zachary K Winkelmann et al.
Background: Research findings must be representative by creating a sample of individuals, ensuring the results can be generalized and applicable to a larger population, which has historically been guided by a power analys...
Machine learning models explanations as interpretations of evidence: a theoretical framework of explainability and its implications on high-stakes biomedical decision-making [0.03%]
机器学习模型解释作为证据的诠释：可解释性理论框架及其对高风险生物医学决策的影响
Matteo Rizzo,Alberto Veneri,Matteo Marcuzzo et al.
Matteo Rizzo et al.
Explainable Artificial Intelligence, or XAI, is a vibrant research topic in the artificial intelligence community. It is raising growing interest across methods and domains, especially those involving high-stakes decision-making, such as th...
A comparative evaluation of sufficient dimension reduction and traditional statistical methods for composite biomarker score construction in diagnostic classification [0.03%]
降维方法与传统统计方法在诊断分类中的复合生物标志物评分构建方面的比较评估研究
Hulya Ozen,Ertugrul Colak,Dogukan Ozen
Hulya Ozen
Background: Combining multiple biomarkers into a single diagnostic score can improve disease classification. However, traditional methods such as logistic regression and linear discriminant analysis depend on restrictive ...
AI-powered classification and network analysis for knowledge mapping in medicine: a century of neurosyphilis research [0.03%]
用于医学知识图谱的自动分类和网络分析：一个世纪的神经梅毒研究
Justine Falciola,Myriam Lamrayah,François R Herrmann et al.
Justine Falciola et al.
Comparative effectiveness research with average hazard for censored time-to-event outcomes: simulation study and application to observational data [0.03%]
基于观察性数据的平均危害比率的非劣效性检验：模拟研究与应用
Hong Xiong,Jean Connors,Deb Schrag et al.
Hong Xiong et al.
Recruitment of a probability-based general population health panel for public health research in Germany: the panel 'Health in Germany' [0.03%]
德国公共卫生研究中的概率人口健康小组的招募：《德国卫生》专题面板的研究
Johannes Lemcke,Ilter Öztürk,Stefan Damerow et al.
Johannes Lemcke et al.
Background: This report presents the study design and recruitment outcomes for the 'Health in Germany' panel, a long-term population-based health survey infrastructure developed by the Robert Koch Institute. The initial r...
Unmeasured confounding and misclassification in studies estimating vaccine effectiveness against hospitalisation and death using electronic health records (EHRs): an evaluation of a multi-country European retrospective cohort study [0.03%]
基于电子健康档案(EHR)的住院和死亡疫苗效果估计研究中的未测量混杂偏倚与错误分类：一项多国欧洲回顾性队列研究报告评估
James Humphreys,Nathalie Nicolay,Toon Braeye et al.
James Humphreys et al.
Background: Electronic health record (EHR)-based observational studies can rapidly provide real-world data on vaccine effectiveness (VE), though EHR data may be prone to misclassification and unmeasured confounding. ...