Capability of chatbots powered by large language models to support the screening process of scoping reviews: a feasibility study [0.03%]
大型语言模型驱动的聊天机器人支持范围审查筛选过程的能力：一项可行性研究
Kim Nordmann,Michael Schaller,Stefanie Sauter et al.
Kim Nordmann et al.
Objectives: The surge in publications increases screening time required to maintain high-quality literature reviews. One of the most time-consuming phases is title and abstract screening. Machine learning tools have semi-...
Language concordance in the digital collection of patient-reported outcome measures [0.03%]
数字患者报告结果测量集合中的语言一致性
Jason B Liu,Brittany M Dacier,Brittany M Dragonetti et al.
Jason B Liu et al.
Objectives: To describe a health system's experience administering patient-reported outcome measures (PROMs) to patients with a non-English preferred language (NEPL). ...
Case Reports
JAMIA open. 2026 Jan 7;9(1):ooaf180. DOI:10.1093/jamiaopen/ooaf180 2026
Comparing the effectiveness of a medication knowledge base product as designed with real-world hospital implementations using the Leapfrog Group's Computerized Physician Order Entry (CPOE/EHR) Evaluation Tool [0.03%]
使用Leapfrog集团的计算机医师订单录入/电子健康记录评估工具比较药物知识库产品设计与实际应用的有效性
Zoe Co,Howard R Strasberg,Bruce R Hanway et al.
Zoe Co et al.
Objectives: We sought to compare and analyze the performance of a medication knowledge base (MKB) vendor's (Medi-Span) fully enabled, factory settings product to operational implementations in hospitals using the Leapfrog...
Mark A Kramer,Aanchal Mathur,Caroline E Adams et al.
Mark A Kramer et al.
Objective: To explore the use of large language models (LLMs) to assist in developing new agent-based disease-specific patient journey models. Materials a...
Real-time clinical analytics at scale: a platform built on large language models-powered knowledge graphs [0.03%]
大规模实时临床分析：基于大型语言模型驱动的知识图平台
Shuang Cao,Rui Li,Rui Wu et al.
Shuang Cao et al.
Objectives: The increasing volume of clinical trial documents presents a significant challenge for biomedical researchers who must analyze vast amounts of unstructured and structured data. Traditional methods are no longe...
Developing updated and new guidance to promote reliable patient identification [0.03%]
促进可靠患者身份识别的更新和新指南的制定
Emma Weatherford,Anne Grauer,Carina Sirochinsky et al.
Emma Weatherford et al.
Objectives: To describe the process of updating the Patient Identification Safety Assurance Factors for EHR Resilience (SAFER) Guide and to review new practices and refinements to the Guide. ...
Case Reports
JAMIA open. 2026 Jan 6;9(1):ooaf160. DOI:10.1093/jamiaopen/ooaf160 2026
Artificial intelligence for personalized management of vestibular schwannoma: a multidisciplinary clinical implementation study [0.03%]
面向听神经瘤的个性化管理的人工智能应用：一项多学科临床实践研究
Navodini Wijethilake,Steve Connor,Anna Oviedova et al.
Navodini Wijethilake et al.
Objectives: Management of patients with vestibular schwannoma (VS) relies on precise tumor size and growth trend evaluation. We introduce and evaluate a novel computer-assisted reporting tool for clinical decision support...
Developing an artificial intelligence-powered question-and-answer chatbot with English-Spanish capabilities for new mothers [0.03%]
一种具有英西双语功能的面向新生母亲的人工智能问答回答机器人开发项目
Quynh C Nguyen,Elizabeth M Norell,Heran Mane et al.
Quynh C Nguyen et al.
Objectives: Generative AI chatbots are revolutionizing health education by making complex information more accessible to the public. However, their use presents risks, including bias, hallucinations, ethical concerns, and...
Leveraging ChatGPT for thematic analysis of medical best practice advisory data [0.03%]
利用ChatGPT进行医学最佳实践咨询数据主题分析
Yejin Jeong,Margaret Smith,Robert J Gallo et al.
Yejin Jeong et al.
Objectives: To evaluate ChatGPT's ability to perform thematic analysis of medical Best Practice Advisory (BPA) free-text comments and identify prompt engineering strategies that optimize performance. ...
Development of a risk factor framework to inform machine learning prediction of young people's mental health problems: a Delphi study [0.03%]
一项关于青年心理问题的机器学习预测风险因素框架的发展：德尔菲研究
Katherine Parkin,Ryan Crowley,Rachel Sippy et al.
Katherine Parkin et al.
Objectives: To create a theoretical framework of mental health risk factors to inform the development of prediction models for young people's mental health problems. ...