Predicting falls using electronic health records: a time series approach [0.03%]
基于电子健康档案的时间序列跌倒预测模型研究
Peter J Hoover,Terri L Blumke,Anna D Ware et al.
Peter J Hoover et al.
Objective: To develop a more accurate fall prediction model within the Veterans Health Administration. Materials and methods: The cohor...
Synthetic data for pharmacogenetics: enabling scalable and secure research [0.03%]
合成的药物基因组学数据：实现可扩展且安全的研究
Marko Miletic,Anna Bollinger,Samuel S Allemann et al.
Marko Miletic et al.
Objective: This study evaluates the performance of 7 synthetic data generation (SDG) methods-synthpop, avatar, copula, copulagan, ctgan, tvae, and the large language models-based tabula-for supporting pharmacogenetics (PG...
Early auxiliary diagnosis model for chest pain triad based on artificial intelligence multimodal fusion [0.03%]
基于人工智能多模态融合的胸痛三联征早期辅助诊断模型
Jun Tang,Fang Chen,Dongdong Wu
Jun Tang
Objectives: Acute chest pain is a common presentation in the emergency department, characterized by sudden onset with high morbidity and mortality. Traditional diagnostic methods, such as computed tomography (CT) and CT a...
Leveraging open-source large language models for clinical information extraction in resource-constrained settings [0.03%]
在资源受限环境下利用开源大规模语言模型进行临床信息提取
Luc Builtjes,Joeran Bosma,Mathias Prokop et al.
Luc Builtjes et al.
Objective: We aimed to evaluate the zero-shot performance of open-source generative large language models (LLMs) on clinical information extraction from Dutch medical reports using the Diagnostic Report Analysis: General ...
Workflows to automate covariate-adaptive randomization in REDCap via data entry triggers [0.03%]
利用数据触发器在REDCap中通过自动化的协变量自适应随机化的工作流
Jacob M Schauer,Marc O Broxton,Luke V Rasmussen et al.
Jacob M Schauer et al.
Objective: Covariate-adaptive randomization algorithms (CARAs) can reduce covariate imbalance in randomized controlled trials (RCTs), but a lack of integration into Research Electronic Data Capture (REDCap) has limited th...
Automated phenotyping of congenital heart disease for dynamic patient aggregation and outcome reporting [0.03%]
先天性心脏病的自动表型分型以进行动态患者聚集和结果报告
Shuhei Toba,Taylor M Smith,Francesca Sperotto et al.
Shuhei Toba et al.
Objectives: Accurate characterization of patients with congenital heart disease is fundamental to research, outcomes reporting, quality improvement, and clinical decision-making. Here we present an approach to computing t...
Adding employment status in the medical record demonstrates its importance as a social determinant of health [0.03%]
在医疗记录中增加就业状况以证明其作为健康的社会决定因素的重要性
Laura E Breeher,Samantha Westphal,Tammy Green et al.
Laura E Breeher et al.
Objective: To share findings of a quality improvement initiative to capture employment status in the electronic medical record (EMR) to mitigate the potential impact of work loss on the health of patients by utilizing the...
Evaluating the impact of data biases on algorithmic fairness and clinical utility of machine learning models for prolonged opioid use prediction [0.03%]
评估数据偏差对算法公平性及机器学习模型预测长期阿片类药物使用临床效用的影响
Behzad Naderalvojoud,Catherine Curtin,Steven M Asch et al.
Behzad Naderalvojoud et al.
Objectives: The growing use of machine learning (ML) in healthcare raises concerns about how data biases affect real-world model performance. While existing frameworks evaluate algorithmic fairness, they often overlook th...
Developing a real-time registry to track breast cancer patients across the city of Boston [0.03%]
开发一个实时注册系统，以追踪波士顿全市的乳腺癌患者
Amy M LeClair,Clara A Chen,Marisa L Mizzoni et al.
Amy M LeClair et al.
Objectives: Patient navigation is designed to identify and address patients' needs throughout their cancer treatment. In the context of a clinical trial designed to deliver a standardized patient navigation protocol, a re...
Adam Rule,Rutvi Shah,Christina Dudley et al.
Adam Rule et al.
Objective: Many primary care physicians (PCPs) feel overwhelmed by the number of electronic health record inbox messages they receive. The objective of this study was to characterize PCPs' experiences with inbox triage-th...