Evaluating large language models for automated REDCap support ticket triage and response [0.03%]
评估大型语言模型在自动REDCap支持票分类和响应中的应用
Andrew Carroll,Dawn Brown,Domenick Silvio et al.
Andrew Carroll et al.
Objectives: To evaluate the utility of large language models (LLMs) without and with retrieval-augmented generation (RAG) resources for automating Research Electronic Data Capture (REDCap) support at a large academic medi...
Disparities in digital information exchange and interoperability among family medicine physicians in the United States [0.03%]
美国初级保健医师间数字信息交换和互操作性差距研究
Kate E Trout,Jeongyoung Park
Kate E Trout
Objective: This study examines disparities in the use of interoperability features within the EHR among family medicine physicians in the United States, particularly in areas with higher social deprivation index and rural...
Strategies for mitigating artificial intelligence bias in healthcare: a systematic review [0.03%]
减轻医疗保健中人工智能偏见的策略：系统评价研究
Kais Gadhoumi,Rashaud Senior,Sijia Wei et al.
Kais Gadhoumi et al.
Objectives: Artificial intelligence is used in healthcare to identify and manage health conditions across diverse patient populations and clinical settings, but biases in algorithms can perpetuate and exacerbate inequalit...
Using large language models to enhance clinically-driven missing data recovery algorithms in electronic health records [0.03%]
利用大型语言模型增强电子健康记录中临床驱动的缺失数据恢复算法
Sarah C Lotspeich,Abbey N Collins,Brian J Wells et al.
Sarah C Lotspeich et al.
Objectives: Electronic health record (EHR) data are prone to missingness and errors. Previously, we devised an enriched chart review protocol where a "roadmap" of auxiliary diagnoses was used to recover missing values. St...
Using sentiment analysis to quantify the relative desirability and acceptability of drug-product attributes [0.03%]
利用情感分析量化药物产品属性的相对吸引力和可接受性
Chiril Calin,Maria Deligianni,Brett R South et al.
Chiril Calin et al.
Objectives: Patient adherence to medication may be influenced by preferences regarding drug-product attributes. Product quality complaints (PQC) and medical information (MI) requests are a potential source of evidence on ...
Eero Korpela,Leah H Rubin,Raha M Dastgheyb et al.
Eero Korpela et al.
Objective: To develop a freely available, researcher-oriented system for accurate normalization of free-text medication strings to standardized RxNorm ingredient-level concepts. ...
Assessing data quality of inflammatory bowel disease patients in the All of Us research program [0.03%]
评估炎症性肠病患者在"全民参与研究计划"中的数据质量
Matthew Spotnitz,Adam S Faye,John Giannini et al.
Matthew Spotnitz et al.
Purpose: Inflammatory bowel disease (IBD) consists of Crohn's disease (CD) and ulcerative colitis (UC) and is a spectrum autoimmune disease of the gastrointestinal tract. Large scale real-world evidence studies could prov...
Intelligent documentation in medical education: can AI replace manual case logging? [0.03%]
智能医学教育：人工智能能否取代手动病例记录？
Nafiz Imtiaz Khan,Kiley Cleland,Vladimir Filkov et al.
Nafiz Imtiaz Khan et al.
Objective: This study investigates the feasibility of using large language models (LLMs) to automate procedural case log documentation in radiology training. We evaluate whether AI can replace manual logging, identify whi...
i2b2-ML: module to facilitate machine learning in the informatics for integrating biology and the bedside platform [0.03%]
i2b2-ML：一个支持床旁生物学集成信息学平台的机器学习模块
Jeffery G Klann,Micheal M Mendis,Shyam Visweswaran et al.
Jeffery G Klann et al.
Objective: Although machine learning (ML) holds significant potential to transform healthcare, there has been a recent surge in research output that often lacks methodological rigor, contributing to a reproducibility cris...
Content matters, context matters: unraveling behavior dynamics in an online health community for tobacco cessation [0.03%]
内容重要，环境亦然：解开线上烟草戒断社区的行为动力学
Tavleen Singh,Runzhi Zhou,Kayo Fujimoto et al.
Tavleen Singh et al.
Objectives: The objective of this research was to examine the content and context-specific information diffusion patterns underlying communication pertaining to tobacco use from online health communities (OHCs). ...