Optimal large language models to screen citations for systematic reviews [0.03%]
最优的大规模语言模型用于系统评价引文筛选
Takehiko Oami,Yohei Okada,Taka-Aki Nakada
Takehiko Oami
Recent studies highlight the potential of large language models (LLMs) in citation screening for systematic reviews; however, the efficiency of individual LLMs for this application remains unclear. This study aimed to compare accuracy, time...
Knowledge user involvement is still uncommon in published rapid reviews-a meta-research cross-sectional study [0.03%]
知识用户参与快速回顾发表仍不常见——一项元研究横断面调查研究
Barbara Nussbaumer-Streit,Dominic Ledinger,Christina Kien et al.
Barbara Nussbaumer-Streit et al.
Background: Involving knowledge users (KUs) such as patients, clinicians, or health policymakers is particularly relevant when conducting rapid reviews (RRs), as they should be tailored to decision-makers' needs. However,...
Trials and triangles: Network meta-analysis of multi-arm trials with correlated arms [0.03%]
相关性处理：多臂临床试验的网状Meta分析研究
Gerta Rücker,Guido Schwarzer
Gerta Rücker
For network meta-analysis (NMA), we usually assume that the treatment arms are independent within each included trial. This assumption is justified for parallel design trials and leads to a property we call consistency of variances for both...
NMAsurv: An R Shiny application for network meta-analysis based on survival data [0.03%]
基于生存数据的网络-meta分析R shiny应用(NMA-surv)
Taihang Shao,Mingye Zhao,Fenghao Shi et al.
Taihang Shao et al.
Network meta-analysis (NMA) is becoming increasingly important, especially in the field of medicine, as it allows for comparisons across multiple trials with different interventions. For time-to-event data, that is, survival data, tradition...
Danni Xia,Honghao Lai,Weilong Zhao et al.
Danni Xia et al.
This study aims to explore the feasibility and accuracy of utilizing large language models (LLMs) to assess the risk of bias (ROB) in cohort studies. We conducted a pilot and feasibility study in 30 cohort studies randomly selected from ref...
StudyTypeTeller-Large language models to automatically classify research study types for systematic reviews [0.03%]
研究类型识别器——用于系统评价的研究类型的自动分类的大语义模型
Simona Emilova Doneva,Shirin de Viragh,Hanna Hubarava et al.
Simona Emilova Doneva et al.
screening, a labor-intensive aspect of systematic review, is increasingly challenging due to the rising volume of scientific publications. Recent advances suggest that generative large language models like generative pre-trained transformer...
Meta-analyzing correlation matrices in the presence of hierarchical effect size multiplicity [0.03%]
在存在层次效应大小多重性的情况下分析相关矩阵的元分析
Ronny Scherer,Diego G Campos
Ronny Scherer
To synthesize evidence on the relations among multiple constructs, measures, or concepts, meta-analyzing correlation matrices across primary studies has become a crucial analytic approach. Common meta-analytic approaches employ univariate o...
Combining search filters for randomized controlled trials with the Cochrane RCT Classifier in Covidence: a methodological validation study [0.03%]
Covidence中结合随机对照试验的筛选条件和Cochrane RCT分类器的方法学验证研究
Klas Moberg,Carl Gornitzki
Klas Moberg
Our objective was to evaluate the recall and number needed to read (NNR) for the Cochrane RCT Classifier compared to and in combination with established search filters developed for Ovid MEDLINE and Embase.com. A gold standard set of 1,103 ...
Regression augmented weighting adjustment for indirect comparisons in health decision modelling [0.03%]
基于回归扩充的加权调整在健康决策模型中的间接比较方法研究
Chengyang Gao,Anna Heath,Gianluca Baio
Chengyang Gao
Background: Understanding the relative costs and effectiveness of all competing interventions is crucial to informing health resource allocations. However, to receive regulatory approval for efficacy, novel pharmaceutical...
Translating systematic searches in the APA PsycInfo database from Ovid to EBSCOhost: A tutorial based on a filter translation [0.03%]
从OVID到EBSCOHOST的APAPsycInfo数据库系统检索转换教程——基于一种过滤器翻译
Zahra Premji,Hilary Kraus
Zahra Premji
Search filters are single-concept systematic search strategies created by experts. Filters are a valuable resource for systematic searchers. Typically, filters are designed for a single database in a single interface. If researchers do not ...