Characterizing physicians' information needs related to a gap in knowledge unmet by current evidence [0.03%]
描述医生与现有证据无法满足的知识缺口相关的信息需求
Anna Ostropolets,RuiJun Chen,Linying Zhang et al.
Anna Ostropolets et al.
Objective: The study sought to explore information needs arising from a gap in clinicians' knowledge that is not met by current evidence and identify possible areas of use and target groups for a future clinical decision ...
Organizational diagnostics: a systematic approach to identifying technology and workflow issues in clinical settings [0.03%]
组织诊断：系统识别临床环境中技术和工作流程问题的方法
Kim M Unertl,Laurie Lovett Novak,Courtney Van Houten et al.
Kim M Unertl et al.
Objectives: Healthcare organizations need to rapidly adapt to new technology, policy changes, evolving payment strategies, and other environmental changes. We report on the development and application of a structured meth...
Modified early warning score-based clinical decision support: cost impact and clinical outcomes in sepsis [0.03%]
基于修改早期预警评分的临床决策支持系统：脓毒症中的成本影响和临床结果
Devin J Horton,Kencee K Graves,Polina V Kukhareva et al.
Devin J Horton et al.
Objective: The objective of this study was to assess the clinical and financial impact of a quality improvement project that utilized a modified Early Warning Score (mEWS)-based clinical decision support intervention targ...
Machine learning for early detection of sepsis: an internal and temporal validation study [0.03%]
机器学习在脓毒症早期检测中的应用：一项内部和时间验证研究
Armando D Bedoya,Joseph Futoma,Meredith E Clement et al.
Armando D Bedoya et al.
Objective: Determine if deep learning detects sepsis earlier and more accurately than other models. To evaluate model performance using implementation-oriented metrics that simulate clinical practice. ...
Estimating real-world performance of a predictive model: a case-study in predicting mortality [0.03%]
预测模型在现实世界性能的评估：一项关于死亡率预测的案例研究
Vincent J Major,Neil Jethani,Yindalon Aphinyanaphongs
Vincent J Major
Objective: One primary consideration when developing predictive models is downstream effects on future model performance. We conduct experiments to quantify the effects of experimental design choices, namely cohort select...
Medication adherence for atrial fibrillation patients: triangulating measures from a smart pill bottle, e-prescribing software, and patient communication through the electronic health record [0.03%]
房颤患者的药物依从性：通过智能药瓶、电子处方软件和电子健康记录中的患者沟通来确定测量值
Tammy Toscos,Michelle Drouin,Jessica A Pater et al.
Tammy Toscos et al.
Objective: Our primary objectives were to examine adherence rates across two technologies (e-prescribing software and smart pill bottle) with cross-validation from alert-triggered messaging within the patient electronic h...
Artificial intelligence-based conversational agent to support medication prescribing [0.03%]
基于人工智能的会话代理以支持药物开处方
Anita M Preininger,Brett South,Jeff Heiland et al.
Anita M Preininger et al.
Objective: This article describes the system architecture, training, initial use, and performance of Watson Assistant (WA), an artificial intelligence-based conversational agent, accessible within Micromedex®. ...
ClinicNet: machine learning for personalized clinical order set recommendations [0.03%]
ClinicNet：机器学习用于个性化临床指令集推荐
Jonathan X Wang,Delaney K Sullivan,Alex C Wells et al.
Jonathan X Wang et al.
Objective: This study assesses whether neural networks trained on electronic health record (EHR) data can anticipate what individual clinical orders and existing institutional order set templates clinicians will use more ...
Evaluation of an artificial intelligence clinical trial matching system in Australian lung cancer patients [0.03%]
澳大利亚肺癌患者人工智能临床试验匹配系统评价研究
Marliese Alexander,Benjamin Solomon,David L Ball et al.
Marliese Alexander et al.
Objective: The objective of this technical study was to evaluate the performance of an artificial intelligence (AI)-based system for clinical trials matching for a cohort of lung cancer patients in an Australian cancer ho...
The anatomy of a distributed predictive modeling framework: online learning, blockchain network, and consensus algorithm [0.03%]
分布式预测建模框架的构成要素：在线学习、区块链网络和共识算法
Tsung-Ting Kuo
Tsung-Ting Kuo
Objective: Cross-institutional distributed healthcare/genomic predictive modeling is an emerging technology that fulfills both the need of building a more generalizable model and of protecting patient data by only exchang...