文章摘要

马费成,周利琴.面向智慧健康的知识管理与服务[J].中国图书馆学报,2018,44(5):4~19
面向智慧健康的知识管理与服务
Knowledge Management and Services for Smart Health
投稿时间:2018-08-09  修订日期:2018-03-21
DOI:
中文关键词: 智慧健康  知识管理  知识服务  公众健康知识库  个人健康大数据  用户画像
英文关键词: Smart health  Knowledge management  Knowledge service  Consumer health knowledge base  Personal health big data  User profile
基金项目:本文系国家自然科学基金国际(地区)合作与交流项目“基于慢病知识管理的智慧养老平台研究”(编号:71661167007)和国家自然科学基金重点国际(地区)合作研究项目“大数据环境下的知识组织与服务创新”(编号:71420107026)的研究成果之一
作者单位E-mail
马费成 武汉大学信息管理学院教授、信息资源研究中心首席科学家教授博士生导师。 湖北 武汉 430072 fchma@whu.edu.cn,fchma@whu.edu.cn 
周利琴 武汉大学信息管理学院博士研究生。 湖北 武汉 430072  
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中文摘要:
      智慧健康是一种全新的医疗保健模式,对其产生的海量、异构、多源健康大数据进行有效的获取、组织、查询与分析,是实现健康保健“智慧化”的关键。在把握智慧健康知识管理的内涵、定位、目标及体系架构的基础上,探究面向智慧健康的领域知识库构建、健康数据管理分析平台的建设与实施、知识服务机制等问题,提出从本体库构建的粗粒度匹配、多种知识融合模式的细粒度匹配及用户画像构建三种方案的知识服务机制,并指出面向智慧健康知识管理与服务研究需要进一步突破与落实的方向。图5。 参考文献44。
英文摘要:
With the rapid development and integration of modern information technologies (such as Big data, Cloud computing, Internet of Things, and Mobile Internet), waves of “Internet + medical” and artificial intelligence have swept the world, driven rapid expansion of health intelligent terminals, and promoted intelligent transformation of healthcare related products. The traditional “disease centered post treatment” model cannot solve problems of continuous healthcare and chronic disease management. It is necessary to establish a “health oriented big health concept” as an overall response to a wide range of health influencing factors, and create a “knowledge prevention medical care foster” integrating Smart Health models in health tracking, prediction, disease prevention, patient health management and personalized treatment in an all round and life cycle way. However, there exists a common problem: the spatial distribution, composition structure, type format and representation of the massive, heterogeneous and multi source health data are becoming more and more complicated and make medical information management particularly difficult. How do we effectively obtain, organize, query and analyze a large number of health data and successfully apply them to modern medicine?
This study aims to apply knowledge management, knowledge service theory and methods from the field of information resources and management to the field of Smart Health through constructing the Public Health Knowledge Base and Personal Health Big Data Management Platform to integrate decentralized personal health data, medical data, and smart health knowledge. On the basis of grasping the connotation, orientation, objectives and system structure of smart health knowledge management, the Public Health Knowledge Base is designed based on the construction of Knowledge Graph in an open network environment, which provides decision support for smart health service. The process can be divided into steps of health information collection, health knowledge extraction, representation, organization, assessment, and fusion. In addition, the Personal Health Big Data Management Platform is constructed to monitor the physical state of the public, assist doctors in making accurate diagnosis and medication decisions, and even remind patients toquit bad habits. On this foundation, the smart health knowledge service mechanism is constructed based on user need and health portraits. The coarse grained matching based on ontology, fine grained matching based on multiple knowledge fusion, and user portrait construction pattern are proposed to provide smart health knowledge service for the public, medical and nursing staff, and professional medical institutions.
In summary, constructing the Public Health Knowledge Base, the Personal Health Big Data Management Platform and the smart health knowledge service mechanism can facilitate monitoring and understanding health status in real time, and push smart health knowledge to achieve self health management, although the research we have done is basic and theoretical exploration. In order to realize the Health China strategy of “constructing and sharing, the health of whole people”, it is necessary to raise the Smart Health to the national strategic level. Closely combined the great advantages of intelligent city, standing at the strategic height, Smart Health must make breakthroughs in four aspects: 1) Strengthening the construction of think tanks in the field of Smart Health; 2) Establishing Standards for Smart Health Data and enhancing healthcare data collection; 3) Promoting the utilization and sharing of personal health big data; 4) emphasizing user demands and forming a smart health industrial system covering the whole life cycle. 5 figs. 44 refs.




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