Development of a dynamic prediction model for unplanned ICU admission and mortality in hospitalized patients [0.03%]
住院患者的非计划入住ICU和死亡的动态预测模型的开发
Davide Placido,Hans-Christian Thorsen-Meyer,Benjamin Skov Kaas-Hansen et al.
Davide Placido et al.
Frequent assessment of the severity of illness for hospitalized patients is essential in clinical settings to prevent outcomes such as in-hospital mortality and unplanned admission to the intensive care unit (ICU). Classical severity scores...
Public interest trends for Covid-19 and alignment with the disease trajectory: A time-series analysis of national-level data [0.03%]
新冠疫情下的公众兴趣趋势及其与疫情发展吻合程度的分析：基于全国数据的时间序列研究
Panayiotis D Ziakas,Eleftherios Mylonakis
Panayiotis D Ziakas
Data from web search engines have become a valuable adjunct in epidemiology and public health, specifically during epidemics. We aimed to explore the concordance of web search popularity for Covid-19 across 6 Western nations (United Kingdom...
Predicting HIV infection in the decade (2005-2015) pre-COVID-19 in Zimbabwe: A supervised classification-based machine learning approach [0.03%]
新冠肺炎疫情前的十年（2005-2015年）津巴布韦HIV感染预测：一种基于监督分类的机器学习方法
Rutendo Beauty Birri Makota,Eustasius Musenge
Rutendo Beauty Birri Makota
The burden of HIV and related diseases have been areas of great concern pre and post the emergence of COVID-19 in Zimbabwe. Machine learning models have been used to predict the risk of diseases, including HIV accurately. Therefore, this pa...
Validation and implementation of a mobile app decision support system for prostate cancer to improve quality of tumor boards [0.03%]
一种改善前列腺癌肿瘤委员会质量的手机应用程序决策支持系统的验证与实现
Yasemin Ural,Thomas Elter,Yasemin Yilmaz et al.
Yasemin Ural et al.
Certified Cancer Centers must present all patients in multidisciplinary tumor boards (MTB), including standard cases with well-established treatment strategies. Too many standard cases can absorb much of the available time, which can be unf...
Using medicare claims to estimate risk-adjusted performance of Pennsylvania trauma centers [0.03%]
利用医疗保险索赔估计宾夕法尼亚州创伤中心的风险调整性能
Alexis M Zebrowski,Phillipe Loher,David G Buckler et al.
Alexis M Zebrowski et al.
Trauma centers use registry data to benchmark performance using a standardized risk adjustment model. Our objective was to utilize national claims to develop a risk adjustment model applicable across all hospitals, regardless of designation...
Video text messaging is needed to deliver patient education about preventive care in the United States [0.03%]
视频短信在美国传递有关预防保健的患者教育方面是必要的
Gloria D Coronado,Esmeralda Ruiz,Evelyn Torres-Ozadali et al.
Gloria D Coronado et al.
Work unit level personnel working hours and the patients' length of in-hospital stay-An administrative data approach [0.03%]
基于行政数据的科室人员工作时间和患者住院时长关系研究
Oxana Krutova,Jenni Ervasti,Marianna Virtanen et al.
Oxana Krutova et al.
Administrative data accumulating daily from hospitals would provide new possibilities to assess work shifts and patient care. We aimed to investigate associations of work unit level average work shift length and length of patient in-hospita...
People with long-term conditions sharing personal health data via digital health technologies: A scoping review to inform design [0.03%]
长期患病人士通过数字健康技术分享个人健康数据：告知设计的综述研究
Amy Rathbone,Simone Stumpf,Caroline Claisse et al.
Amy Rathbone et al.
The use of digital technology amongst people living with a range of long-term health conditions to support self-management has increased dramatically. More recently, digital health technologies to share and exchange personal health data wit...
Efficacy of Intellect's self-guided anxiety and worry mobile health programme: A randomized controlled trial with an active control and a 2-week follow-up [0.03%]
智力效能的自我引导焦虑和担忧移动健康程序的有效性：一种主动控制下的随机对照试验及为期两周的随访研究
Feodora Roxanne Kosasih,Vanessa Tan Sing Yee,Sean Han Yang Toh et al.
Feodora Roxanne Kosasih et al.
Digital self-guided mobile health [mHealth] applications are cost-effective, accessible, and well-suited to improve mental health at scale. This randomized controlled trial [RCT] evaluated the efficacy of a recently developed mHealth progra...