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Clinical eHealth最新文献

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An anatomization on breast cancer detection and diagnosis employing multi-layer perceptron neural network (MLP) and Convolutional neural network (CNN) 多层感知器神经网络(MLP)和卷积神经网络(CNN)在乳腺癌检测诊断中的应用解剖
Pub Date : 2020-11-24 DOI: 10.1016/j.ceh.2020.11.002
Meha D. Desai, Manan Shah
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引用次数: 157
Comparative anatomization of data mining and fuzzy logic techniques used in diabetes prognosis 数据挖掘与模糊逻辑技术在糖尿病预后中的比较分析
Pub Date : 2020-11-17 DOI: 10.1016/j.ceh.2020.11.001
Harsh Thakkar, Vaishnavi Shah, Hiteshri Yagnik, Manan Shah
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引用次数: 46
The design choices for the development of an Augmented Reality game for people with visuospatial neglect 为有视觉空间忽视的人开发增强现实游戏的设计选择
Pub Date : 2020-11-17 DOI: 10.1016/j.ceh.2020.11.003
M. Bakker, N. Boonstra, T. Nijboer, M. Holstege, W. Achterberg, Niels H Chavannes
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引用次数: 10
REducing Delay through edUcation on eXacerbations (REDUX) in patients with COPD: a pilot study 通过COPD患者急性加重教育(REDUX)减少延迟:一项试点研究
Pub Date : 2020-08-15 DOI: 10.1016/j.ceh.2020.07.001
Cynthia Hallensleben, E. Meijer, J. Biewenga, R. M. Kievits-Smeets, M. Veltman, Xiaoyue Song, J. V. Boven, N. Chavannes
{"title":"REducing Delay through edUcation on eXacerbations (REDUX) in patients with COPD: a pilot study","authors":"Cynthia Hallensleben, E. Meijer, J. Biewenga, R. M. Kievits-Smeets, M. Veltman, Xiaoyue Song, J. V. Boven, N. Chavannes","doi":"10.1016/j.ceh.2020.07.001","DOIUrl":"https://doi.org/10.1016/j.ceh.2020.07.001","url":null,"abstract":"","PeriodicalId":100268,"journal":{"name":"Clinical eHealth","volume":"56 1","pages":"63-68"},"PeriodicalIF":0.0,"publicationDate":"2020-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73941075","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
A large-scale clinical validation study using nCapp cloud plus terminal by frontline doctors for the rapid diagnosis of COVID-19 and COVID-19 pneumonia in China 一线医生使用nCapp云加终端快速诊断COVID-19和COVID-19肺炎的大规模临床验证研究
Pub Date : 2020-08-11 DOI: 10.1016/j.ceh.2022.07.004
Dawei Yang, Tao Xu, Xun Wang, Deng Chen, Ziqiang Zhang, Lichuan Zhang, Jie Liu, Kui Xiao, Li Bai, Yong Zhang, Lin Zhao, L. Tong, Chao-min Wu, Yaoli Wang, C. Dong, M. Ye, Yu Xu, Zhenju Song, Hong Chen, Jing Li, Jiwei Wang, F. Tan, Hai-tao Yu, Jian Zhou, Jinming Yu, Chunhua Du, Hongqing Zhao, Yu Shang, Linian Huang, Jianping Zhao, Yang Jin, C. Powell, Yuanlin Song, Chunxue Bai
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引用次数: 3
Chinese experts’ consensus on the Internet of Things-aided diagnosis and treatment of coronavirus disease 2019 (COVID-19) 中国专家对2019冠状病毒病(COVID-19)物联网辅助诊疗的共识
Pub Date : 2020-03-17 DOI: 10.1016/j.ceh.2020.03.001
Li Bai, Dawei Yang, Xun Wang, Lin Tong, Xiaodan Zhu, N. Zhong, C. Bai, C. Powell, Rongchang Chen, Jian Zhou, Yuanlin Song, Xin Zhou, Huili Zhu, B. Han, Qiang Li, G. Shi, Shengqing Li, Changhui Wang, Z. Qiu, Yong Zhang, Yu Xu, Jie Liu, Ding Zhang, Chao-min Wu, Jing Li, Jinming Yu, Jiwei Wang, C. Dong, Yaoli Wang, Qi Wang, Lichuan Zhang, Min Zhang, Xia Ma, Lin Zhao, Wencheng Yu, T. Xu, Yang Jin, Xiongbiao Wang, Yuehong Wang, Yan Jiang, Hong Chen, Kui Xiao, Xiaoju Zhang, Zhenju Song, Ziqiang Zhang, Xueling Wu, Jiayuan Sun, Yao Shen, M. Ye, C. Tu, Jinjun Jiang, Hai-tao Yu, F. Tan
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引用次数: 172
Prospect and application of Internet of Things technology for prevention of SARIs 物联网技术预防sars的前景与应用
Pub Date : 2020-02-07 DOI: 10.1016/j.ceh.2020.02.001
Yuanlin Song, Jinjun Jiang, Xun Wang, Dawei Yang, C. Bai
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引用次数: 44
A pilot study of the ‘PSGCloud’ — A cloud-based care service delivery and sleep disorders diagnosis system. Part I: Sleep structure and arousal analysis “PSGCloud”的试点研究——基于云的护理服务提供和睡眠障碍诊断系统。第一部分:睡眠结构和觉醒分析
Pub Date : 2020-01-01 DOI: 10.1016/j.ceh.2020.04.001
Na Wu, Yan Li, Shan Wang, Ying Duan, Li-Qun Xu, He Gao
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引用次数: 0
Chinese experts’ consensus on the Internet of Things-aided diagnosis and treatment of coronavirus disease 2019 (COVID-19) 中国专家对2019冠状病毒病(COVID-19)物联网辅助诊疗的共识
Pub Date : 2020-01-01 DOI: 10.1016/j.ceh.2020.03.001
Li Bai , Dawei Yang , Xun Wang , Lin Tong , Xiaodan Zhu , Nanshan Zhong , Chunxue Bai , Charles A. Powell , Rongchang Chen , Jian Zhou , Yuanlin Song , Xin Zhou , Huili Zhu , Baohui Han , Qiang Li , Guochao Shi , Shengqing Li , Changhui Wang , Zhongmin Qiu , Yong Zhang , Fei Tan

The aim is to diagnose COVID-19 earlier and to improve its treatment by applying medical technology, the “COVID-19 Intelligent Diagnosis and Treatment Assistant Program (nCapp)” based on the Internet of Things. Terminal eight functions can be implemented in real-time online communication with the “cloud” through the page selection key. According to existing data, questionnaires, and check results, the diagnosis is automatically generated as confirmed, suspected, or suspicious of 2019 novel coronavirus (2019-nCoV) infection. It classifies patients into mild, moderate, severe or critical pneumonia. nCapp can also establish an online COVID-19 real-time update database, and it updates the model of diagnosis in real time based on the latest real-world case data to improve diagnostic accuracy. Additionally, nCapp can guide treatment. Front-line physicians, experts, and managers are linked to perform consultation and prevention. nCapp also contributes to the long-term follow-up of patients with COVID-19. The ultimate goal is to enable different levels of COVID-19 diagnosis and treatment among different doctors from different hospitals to upgrade to the national and international through the intelligent assistance of the nCapp system. In this way, we can block disease transmission, avoid physician infection, and epidemic prevention and control as soon as possible.

目的是利用医疗技术,即基于物联网的“新冠肺炎智能诊疗辅助项目(nCapp)”,更早地诊断新冠肺炎,提高治疗水平。终端八功能可通过页面选择键实现与“云”的实时在线通信。根据现有数据、问卷调查和检查结果,自动生成2019年新型冠状病毒(2019- ncov)感染确诊、疑似或可疑诊断。它将患者分为轻度、中度、重度和危重性肺炎。nCapp还可以建立在线COVID-19实时更新数据库,根据最新的真实病例数据实时更新诊断模型,提高诊断准确率。此外,nCapp可以指导治疗。一线医生、专家和管理人员相互联系,进行咨询和预防。nCapp还有助于COVID-19患者的长期随访。最终目标是通过nCapp系统的智能辅助,使不同医院不同医生的新冠肺炎诊疗水平提升到国内和国际水平。这样才能阻断疾病传播,避免医师感染,尽快做好疫情防控工作。
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引用次数: 171
Patient perspectives on the digitization of personal health information in the emergency department: Gaps and opportunities 急诊科患者对个人健康信息数字化的看法:差距与机遇
Pub Date : 2020-01-01 DOI: 10.1016/j.ceh.2020.01.001
Sophia Ly , Kendall Ho
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引用次数: 1
期刊
Clinical eHealth
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