Design and implementation of an end-to-end AI-driven colonoscopy recall workflow at scale [0.03%]
大规模结肠镜检查召回工作的端到端人工智能驱动的设计与实现
Aman Mohapatra,Rachel Porth,Si Wong et al.
Aman Mohapatra et al.
Objectives: To develop a large-language-model (LLM)-centric workflow flow extraction and migration of clinician-documented colonoscopy recall recommendations from unstructured reports and letters during an enterprise-wide...
Follow the data: tracking data quality and completeness in oncology real-world data [0.03%]
跟随数据：追踪肿瘤真实世界数据的质量和完整性
Samantha J App,Anne-Marie Meyer,Shannon Silkensen et al.
Samantha J App et al.
Objectives: Electronic Health Record (EHR) data are increasingly used in cancer research, yet the fidelity of this data when exchanged between systems remains poorly quantified. This study investigated the agreement in es...
The telehealth engagement measure: a proportions-based measure of care delivered via video and phone for research, clinical, and policy assessments [0.03%]
基于比例的远程医疗服务交付测量指标：用于研究、临床和政策评估中的视频和电话服务质量衡量标准
Jacqueline M Ferguson,Donna M Zulman,Ashok Reddy et al.
Jacqueline M Ferguson et al.
Objectives: In the absence of standardized measures, researchers have struggled to define meaningful use of telehealth (care received via video or telephone). We evaluated a novel Telehealth Engagement Measure (TEM) that ...
WeChat in China's mobile health: a bibliometric analysis of trends, hotspots, and academic contributions [0.03%]
微信在中国移动医疗中的作用趋势、热点及学术贡献的文献计量分析
Rui Li,Yin Xie,Tong Wu
Rui Li
Objectives: To use bibliometric methods to deeply analyze the application of WeChat in China's mHealth field, outline its research panorama, and clarify research frontiers. ...
Timely nudges promote patient portal enrollment and sustained engagement: a randomized controlled trial [0.03%]
及时的提示可促进患者登录门户和持续参与：一项随机对照试验
Sasha C Brietzke,Maheen Shermohammed,Amir Goren et al.
Sasha C Brietzke et al.
Objective: Patient portals support health management, yet enrollment remains low. This study evaluated whether timely email nudges increase patient portal enrollment compared with usual system portal invitations, whether ...
Area-specific autoencoder spatiotemporal graph neural networks for opioid overdose death prediction [0.03%]
基于领域自适应自动编码器的时空图神经网络在阿片类药物致死预测中的应用研究
Xianhui Chen,Changchang Yin,John V Myers et al.
Xianhui Chen et al.
Background: Ohio has been severely impacted by the opioid crisis, with opioid overdose (OD) death rates exceeding national averages. Accurate OD death prediction supports proactive prevention and treatment allocation. Exi...
Large language models for automated and audience-tailored labeling of latent classes [0.03%]
大规模语言模型的自动和受众定制的潜在类别标签生成方法
Fatemeh Gholi Zadeh Kharrat,Rob Werfelmann,Glen Ep Ropella et al.
Fatemeh Gholi Zadeh Kharrat et al.
Objective: This study compares multiple LLMs, including ChatGPT, DeepSeek, and Llama, to generate meaningful, audience-adapted labels for the existing latent classes among patients with chronic low back pain (cLBP). ...
Harry B Burke,Albert Hoang,Heidi King et al.
Harry B Burke et al.
Background: The pandemic dramatically increased in the frequency of audiovisual medical visits and the rate of audiovisual visits remains higher than before the pandemic. These visits have the potential to be an important...
Exploring nurses' documentation prioritization strategies to alleviate EHR documentation burden: a phenomenological study [0.03%]
探索护理人员电子病历记录优先策略以减轻负担：现象学研究
Rosemary Mugoya,Jennifer Thate,Fan Hao et al.
Rosemary Mugoya et al.
Objective: This study aims to understand how inpatient nurses determine and prioritize necessary documentation within the context of the Excessive Documentation Burden (ExDocBurden) in Electronic Health Records (EHRs). ...
Text mining methods for automated data extraction from health technology assessment reports of medicines using classical natural language processing and generative artificial intelligence [0.03%]
基于经典自然语言处理和生成式人工智能的药品卫生技术评估报告自动化数据提取文本挖掘方法
Jan-Willem Versteeg,Marie L De Bruin,Maarten Schermer et al.
Jan-Willem Versteeg et al.
Objective: This proof of concept for utilizing automatic data extraction methods to extract health technology assessment (HTA) attributes from HTA reports of medicines aimed to explore which attributes could be extracted ...