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Titlebook: Smart Health; International Confer Xiaolong Zheng,Daniel Zeng,Daniel B. Neill Conference proceedings 2014 Springer International Publishing

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发表于 2025-3-21 19:25:52 | 显示全部楼层 |阅读模式
书目名称Smart Health
副标题International Confer
编辑Xiaolong Zheng,Daniel Zeng,Daniel B. Neill
视频video
丛书名称Lecture Notes in Computer Science
图书封面Titlebook: Smart Health; International Confer Xiaolong Zheng,Daniel Zeng,Daniel B. Neill Conference proceedings 2014 Springer International Publishing
描述This book constitutes the refereed proceedings of the International Conference for Smart Health, ICSH 2014, held in Beijing, China, in July 2014. The 21 papers presented together with 4 extended abstracts were carefully reviewed and selected from numerous submissions. The papers are organized in topical sections on information sharing, integrating and extraction; health data analysis and management; clinical and medical data mining; and clinical practice and medical monitoring.
出版日期Conference proceedings 2014
关键词applied computing; data mining; health care information systems; health informatics; health information
版次1
doihttps://doi.org/10.1007/978-3-319-08416-9
isbn_softcover978-3-319-08415-2
isbn_ebook978-3-319-08416-9Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightSpringer International Publishing Switzerland 2014
The information of publication is updating

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Emoticon Analysis for Chinese Health and Fitness Topicste. To complement non-verbal communication, emoticons are frequently used in Chinese online social media, especially in discussions of health and fitness topics. However, limited research has been done to effectively analyze emoticons in a Chinese context. In this study, we developed an emoticon ana
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Diabetes-Related Topic Detection in Chinese Health Websites Using Deep Learningsubsection for patients. However, most of the articles are uncategorized and without a clear topic or theme, resulting in time consuming information seeking experience. To address this issue, we propose an advanced deep learning approach to detect topics for diabetes related articles from health web
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Identifying Adverse Drug Events from Health Social Media: A Case Study on Heart Disease Discussion Fening to patients’ voices in adverse drug event reporting. However, extracting patient adverse drug event reports from social media continues to be a challenge in health informatics research. To utilize the fertile health social media data for drug safety research, we develop advanced information ex
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Analyzing Spatio-temporal Patterns of Online Public Attentions in Emergency Events: A Case Study of the spatio-temporal patterns of public attention and the interactions with media attention and severity of epidemic is still not well studied. Aim to fill this research gap, we chose the H1N1 influenza outbreak in the mainland of China in 2009 as case to study the spatio-temporal patterns of public
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DiabeticLink: An Integrated and Intelligent Cyber-Enabled Health Social Platform for Diabetic Patienated cyber-enabled patient empowerment and decision support tool to promote diabetes prevention and self-management. Most existing tools are scattered and focused on solving a specific problem from a single angle. DiabeticLink offers an integrated and intelligent web-based platform that enables pati
发表于 2025-3-23 01:30:41 | 显示全部楼层
Collaborative Friendship Networks in Online Healthcare Communities: An Exponential Random Graph Modee friendships form in online healthcare communities. This study examines the relationship between collaborative friendship formation and patients’ characteristics. Results from Exponential Random Graph Model (ERGM) analysis indicate that gender homophily doesn’t appear in CFNs, while health homophil
发表于 2025-3-23 05:55:23 | 显示全部楼层
The Impact of Alcohol Intake on Human Beings Health in Chinalth and Nutrition Survey data in a model of regression. We initially used the self assessed health, which was widely used in related studies, in the database as the health variable but obtained controversial result. After that, to test the result we compared the drinking status between participants
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