Improving the quality of nursing care through standardized nursing languages: Call to action across European countries [0.03%]
通过标准化护理语言提升欧洲各国护理质量的行动呼吁
Fabiana Cristina Dos Santos,Fabio D&#x;Agostino,Mikko Härkönen et al.
Fabiana Cristina Dos Santos et al.
Background: Standardized Nursing Languages (SNLs) have enabled nursing assessments and care to be better documented and visible in electronic health records (EHRs). However, its implementation is challenging and heterogen...
What physical examinations are observed during an in-person GP consultation? Automatic extraction using a text-based approach [0.03%]
基于文本的方法自动提取面对面的全科医生咨询中观察到的身体检查项目
Moomna Waheed,Hao Xiong,Kate Tong et al.
Moomna Waheed et al.
Objectives: Teleconsultation is anticipated to have a long-term role in primary care. However, conducting virtual physical examinations is a well-known limitation. To anticipate unmet needs general practitioners (GPs) and...
Predicting prolonged length of stay following revision total knee arthroplasty: A national database analysis using machine learning models [0.03%]
机器学习模型预测翻修全膝关节置换术后长期住院时间：基于国家数据库的分析
Ashish Mittal,Anirudh Buddhiraju,Murad Abdullah Subih et al.
Ashish Mittal et al.
Background: As the number of revision total knee arthroplasty (TKA) continues to rise, close attention has been paid to factors influencing postoperative length of stay (LOS). The aim of this study is to develop generaliz...
Development and validation of machine learning models for predicting cancer-related fatigue in lymphoma survivors [0.03%]
机器学习模型在预测淋巴瘤幸存者癌症相关疲劳中的开发和验证
Yiming Wang,Lv Tian,Wenqiu Wang et al.
Yiming Wang et al.
Background: New cases of lymphoma are rising, and the symptom burden, like cancer-related fatigue (CRF), severely impacts the quality of life of lymphoma survivors. However, clinical diagnosis and treatment of CRF are ina...
Machine learning for predicting duration of surgery and length of stay: A literature review on joint arthroplasty [0.03%]
基于人工神经网络的手术时长和住院时长预测研究综述——以关节置换术为例
Mohammad Chavosh Nejad,Rikke Vestergaard Matthiesen,Iskra Dukovska-Popovska et al.
Mohammad Chavosh Nejad et al.
Introduction: In recent years, different factors such as population aging have caused escalating demand for hip and knee arthroplasty straining already limited hospitals' resources. To address this challenge, focus is put...
Mobile mental health application use, and app feature preferences among individuals with mental disorders in Ethiopia: A cross-sectional survey [0.03%]
埃塞俄比亚精神疾病患者的移动心理健康应用使用及应用程序功能偏好：横断面调查研究
Yonas Deressa Guracho,Susan J Thomas,Khin Than Win
Yonas Deressa Guracho
Background: Mobile health applications have been shown to assist in the treatment of mental illnesses, yet their potential remains underutilized. As supportive care, mental health applications use may be useful tools in i...
Real-life implementation and evaluation of the e-referral system SIPILINK [0.03%]
SIPILINK电子转诊系统的实际应用及评估研究
Aimé Nun,Anne-Isabelle Tropeano,Edouard Flamarion et al.
Aimé Nun et al.
Introduction: General Practitioners (GPs) play a key role of gatekeeper, as they coordinate patients' care. However, most of them reported having difficulty to refer patients to hospital, especially in semi-urgent context...
The patient's perspective on rehabilitation with wireless accelerometers, activity tracking and motivational feedback following knee replacement: A qualitative study prior to a randomised controlled trial (KneeActivity) [0.03%]
膝关节置换术后无线加速度计、活动监测和动机反馈康复的患者视角：随机对照试验（ KneeActivity试验）前定性研究
Cecilie D Skov,Anders Holsgaard-Larsen,Uffe Kock Wiil et al.
Cecilie D Skov et al.
Background: As healthcare systems evolve, individuals are expected to be more involved in managing their health and rehabilitation. A wireless medical accelerometer (SENS motion®) has been developed to collect objective ...
Randomized Controlled Trial
International journal of medical informatics. 2024 Dec:192:105624. DOI:10.1016/j.ijmedinf.2024.105624 2024
Construction and verification of a machine learning-based prediction model of deep vein thrombosis formation after spinal surgery [0.03%]
基于机器学习的脊柱手术后深静脉血栓形成的预测模型的构建与验证
Xingyan Wu,Zhao Wang,Leilei Zheng et al.
Xingyan Wu et al.
Background: Deep vein thromboembolism (DVT) is a common postoperative complication with high morbidity and mortality rates. However, the safety and effectiveness of using prophylactic anticoagulants for preventing DVT aft...
A scalable approach for critical care data extraction and analysis in an academic medical center [0.03%]
学术医学中心重症监护数据提取和分析的可扩展方法
Sebastian Daniel Boie,Falk Meyer-Eschenbach,Fabian Schreiber et al.
Sebastian Daniel Boie et al.
Background: Electronic health records are a valuable asset for research, but their use is challenging due to inconsistencies of records, heterogeneous formats and the distribution over multiple, non-integrated information...