Assessment of 3 standards-based clinical decision support (CDS) tools in an academic electronic health record using Clinical Quality Language, CDS Hooks, and Fast Healthcare Interoperability Resources: a retrospective evaluation [0.03%]
基于标准的临床决策支持工具在学术型电子健康记录中的评估：回顾性评价Clinical Quality Language、CDS Hooks和Fast Healthcare Interoperability Resources的应用效果
Mark Isabelle,Ivan K Ip,Michael Bakhtin et al.
Mark Isabelle et al.
Objectives: To evaluate clinical decision support (CDS) of varying complexities and care settings represented using Health Information Technology (HIT) standards-Clinical Quality Language (CQL) for representing clinical l...
Comparing artificial intelligence- vs clinician-authored summaries of simulated primary care electronic health records [0.03%]
比较人工智能和临床医生编写的模拟初级保健电子健康记录摘要
Lara Shemtob,Abdullah Nouri,Adam Harvey-Sullivan et al.
Lara Shemtob et al.
Objective: To compare clinical summaries generated from simulated patient primary care electronic health records (EHRs) by GPT-4, to summaries generated by clinicians on multiple domains of quality including utility, conc...
Comparison of 2 electronic health record data extraction methods for laboratory tests used in the Veterans Aging Cohort Study Index [0.03%]
退伍军人老龄化队列研究指数中实验室检查的两种电子健康记录数据提取方法比较
Christine Ramsey-Hardy,Melissa Skanderson,Janet P Tate et al.
Christine Ramsey-Hardy et al.
Objective: To compare Observational Medical Outcomes Partnership (OMOP) Logical Observation Identifiers Names and Codes (LOINC) and Veterans Aging Cohort Study (VACS) methods for extracting laboratory chemistry data from ...
Clinical and economic impact of digital dashboards on hospital inpatient care: a systematic review [0.03%]
基于数字仪表板的住院患者护理的临床和经济影响：系统评价研究
Enrico Coiera,Anastasia Chan,Kalissa Brooke-Cowden et al.
Enrico Coiera et al.
Objective: Digital dashboards are used to monitor patients and improve inpatient outcomes in hospital settings. A systematic review assessed the impact of dashboards across five outcomes of hospital mortality, hospital le...
A fair machine learning model to predict flares of systemic lupus erythematosus [0.03%]
一种预测系统性红斑狼疮发作的公平机器学习模型
Yongqiu Li,Lixia Yao,Yao An Lee et al.
Yongqiu Li et al.
Objective: Systemic lupus erythematosus (SLE) is a chronic autoimmune disease that disproportionately affects women and racial/ethnic minority groups. Predicting disease flares is essential for improving patient outcomes,...
Social vulnerability, lower broadband internet access, and rurality associated with lower telemedicine use in U.S. Counties [0.03%]
与美国县的社会脆弱性、较低的宽带互联网接入和农村地区有关的较低的远程医疗服务使用率
Mollie R Cummins,Bob Wong,Neng Wan et al.
Mollie R Cummins et al.
Objective: Our objective was to determine how social vulnerabilities, broadband access, and rurality relate to telemedicine use across the United States through large-scale analysis of real-world telemedicine data. ...
SurgeryLSTM: a time-aware neural model for accurate and explainable length of stay prediction after spine surgery [0.03%]
基于时间感知的神经网络模型预测脊柱手术后准确且可解释的住院时长外科手术LSTM：一种用于在脊柱手术后进行准确且可解释的住院时长预测的时间感知型神经模型
Ha Na Cho,Sairam Sutari,Alexander Lopez et al.
Ha Na Cho et al.
Objective: To develop and evaluate machine learning (ML) models for predicting length of stay (LOS) in elective spine surgery, with a focus on the benefits of temporal modeling and model interpretability. ...
Advancing methodological development of artificial intelligence in patient-centered comparative clinical effectiveness research: Patient-Centered Outcomes Research Institute's unique contribution to research done differently [0.03%]
以患者为中心的比较临床有效性研究中人工智能的方法学进展：病人结果研究所对“另辟蹊径做科研”的独特贡献
Jinghua Ou,Erin Holve
Jinghua Ou
Background: Recent advancements of Artificial Intelligence (AI) are rapidly transforming clinical research. While this technology offers exciting opportunities, it amplifies existing concerns regarding the need for transp...
Comparison of machine learning models to predict loss to follow-up among people with Human Immunodeficiency Virus (HIV) [0.03%]
用于预测人类免疫缺陷病毒(HIV)患者失访的机器学习模型比较
Jessica P Ridgway,Joseph A Mason,Eleanor E Friedman et al.
Jessica P Ridgway et al.
Objective: To compare different machine learning models of loss to follow-up among people with HIV (PWH). Materials and methods: Using ...
Using the Observational Medical Outcomes Partnership Common Data Model for a multi-registry intensive care unit benchmarking federated analysis: lessons learned [0.03%]
利用观察性医学结果合作伙伴通用数据模型进行多注册表重症监护单元基准分析的经验教训
Aasiyah Rashan,Daniel P Püttmann,Nicolette F de Keizer et al.
Aasiyah Rashan et al.
Objective: Federated analysis is a method that allows data analysis to be performed on similar datasets without exchanging any data, thus facilitating international research collaboration while adhering to strict privacy ...