Health professions trainee experiences transitioning to a new Federal Electronic Health Record: applying learning health system principles to support change management in the Veterans Health Administration [0.03%]
学习健康系统原则在退伍军人健康管理局电子病历转换中的应用——培训人员的视角
Ellen A Ahlness,Justin Rucci,Erin Matteau et al.
Ellen A Ahlness et al.
Objective: Electronic health record (EHR) transitions disrupt health system workforces. Health professions trainees (HPTs) play a critical role in providing care yet are under-addressed during transitions. We apply learni...
The governance of health data in the AI era: a scoping review and computational topic model of the global research landscape [0.03%]
人工智能时代的健康数据治理：一项全球研究领域综述和计算主题模型研究
L Raymond Guo,Shuimei Liu
L Raymond Guo
Background: The integration of artificial intelligence (AI) into health care is critically dependent on vast quantities of patient data, igniting an urgent global debate on data ownership, privacy, and governance. While n...
Enhancing prediction of inpatient deterioration by combining clinical and nurse concern features, with or without temporal clustering [0.03%]
结合临床和护士关注特征（有或无时间聚类）以增强住院患者病情恶化的预测能力
Yik-Ki Jacob Wan,Samir E Abdelrahman,Julio C Facelli et al.
Yik-Ki Jacob Wan et al.
Background: Early warning systems (EWSs) help clinicians identify deteriorating patients using clinical data, such as vital signs. However, standard systems struggle to capture nuanced nursing concerns. The Healthcare Pro...
OEMA: ontology-enhanced multi-agent collaboration framework for zero-shot clinical named entity recognition [0.03%]
基于本体增强的多智能体协作框架OEMA用于零样本临床实体识别
Xinli Tao,Xin Dong,Qiang Zhu et al.
Xinli Tao et al.
Objective: With the rapid growth of unstructured clinical narratives in electronic health records (EHRs), clinical named entity recognition (NER) has become a crucial technique for extracting structured medical informatio...
Spectral clustering identifies patterns of chiropractic care in a national longitudinal cohort [0.03%]
基于光谱的聚类分析识别了全国纵向队列中的整骨疗法模式
Monika Ray,Shao-You Fang,Anthony J Lisi et al.
Monika Ray et al.
Objective: Characterise longitudinal patterns of chiropractic visits for neck pain or low back pain by using machine learning (ML) methods and explainable models. ...
Integrating systems thinking and implementation science in biomedical informatics research [0.03%]
在生物医学信息学研究中整合系统思维和实施科学
Craig E Kuziemsky,Mustafa Ozkaynak,Kim M Unertl et al.
Craig E Kuziemsky et al.
Objective: Implementing biomedical informatics (BMI) tools and applications into clinical and other settings remains a significant challenge. Unintended consequences remain common post-implementation. This paper addresses...
PRIMUS: a precision medicine platform reusing clinical trials and registry data to support treatment selection in multiple sclerosis [0.03%]
精准医学平台PRIMUS：重复使用临床试验和注册数据以支持多发性硬化症治疗选择
Stanislas Demuth,Igor Faddeenkov,Julien Paris et al.
Stanislas Demuth et al.
Objectives: The "Projections In Multiple Sclerosis" (PRIMUS) project aims to develop a precision medicine platform enabling neurologists to support therapeutic decisions in multiple sclerosis by visualizing similar patien...
Trustworthy artificial intelligence in predictive medicine: cancer survival analysis using ethical-by-design and explainable artificial intelligence models [0.03%]
值得信赖的人工智能在预测医学中的应用——使用设计时即符合伦理规范且可解释的人工智能模型进行癌症生存分析
Sajede Farahani,Ismaeel A Siddiqui,Asma Taheri et al.
Sajede Farahani et al.
Objectives: This study aims to develop and evaluate a trustworthy and ethical-by-design machine learning (ML) framework for predicting 5-year cancer survival across 10 Surveillance, Epidemiology, and End Results (SEER) ca...
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...