基于语义的老年智慧健康服务主动规则研究

发布时间：2018-04-03 06:25

本文选题：智慧健康　切入点：慢性病　出处：《海南大学》2017年硕士论文

【摘要】：人口老龄化是世界人口发展的普遍趋势,是科学与经济不断发展进步的标志。随着世界老年化趋势的日益加剧,数字化老年健康服务平台关键技术研究是目前世界上研究的一个热点。目前对于老年慢性病存在一个问题:大量的老年慢性病患者在身体不适时不愿意去医院就医,甚至害怕去医院就医。由于老年慢性病群体的特殊性,以及目前智慧健康的新潮性,使得为这类群体提供健康服务的困难性增加。这类用户群体极少能够主动请求服务,在这种情况下则需要主动地向他们提供健康信息服务,因此健康服务的主动性尤其重要。同时在主动服务过程中,由于受众群体存在专业知识匮乏,对病情了解甚少的问题,在信息提供时存在一定的差异,这使得规则的触发率低,以及服务的提供出现质量低下的问题。本文针对这些问题,对智慧健康服务模型、主动规则、语义进行了研究,主要工作如下:1)建立智慧健康服务模型。本文根据现有的智慧服务以及发展趋势,为解决老年慢性病患者的治疗保健问题,提出了一种智慧健康服务模型。智慧健康服务模型能主动性的提供老年慢病患者当前的身体状况,体征控制情况,预警信息,以及相关健康知识等,从而达到主动健康信息服务的目的。2)提出改进的主动性规则。由于健康信息服务受众群体的特殊性,服务的主动性需求必不可少,同时实际应用中存在突发异常体征问题,导致无法提供准确的健康信息服务。因此本文研究了多种主动性规则,并结合实际应用环境,提出一种能够解决突发异常体征问题的改进的主动性规则ECA-Sequence规则。将历史序列的判定加入传统的主动规则,根据历史序列的长短,结合分级预警解决传统规则和其他改进规则无法解决的提供准确信息服务的问题3)提出半主动规则应用模式与知识本体建立。为改善健康信息服务效率,提高规则触发率,同时也满足知识库的层次化结构存储,本文提出半主动规则应用模式及建立糖尿病知识本体库。该本体库的建立能帮助提高规则利用率、解决患者专业知识匮乏的问题。
[Abstract]:Population aging is the universal trend of world population development and the symbol of continuous development and progress of science and economy.With the increasing trend of aging in the world, the research on key technologies of digital elderly health service platform is a hot spot in the world.At present, there is a problem for chronic diseases in the elderly: a large number of patients with chronic diseases in the elderly are not willing to go to the hospital at the right time, and even afraid to go to the hospital.Because of the particularity of the elderly chronic disease group and the new trend of wisdom and health, it is more difficult to provide health services for these groups.Such user groups are rarely able to actively request services, in which case they need to be actively provided with health information services, so the initiative of health services is particularly important.At the same time, in the process of active service, due to the lack of professional knowledge of the audience group, little understanding of the disease, there are certain differences in the provision of information, which makes the trigger rate of the rules low.And poor quality of service delivery.Aiming at these problems, this paper studies the intelligent health service model, active rules and semantics. The main work is as follows: 1) to establish the intelligent health service model.According to the current intelligence service and its development trend, a model of intelligent health service is proposed to solve the problem of health care for the elderly patients with chronic diseases.The intelligent health service model can actively provide the current physical condition, physical sign control, early warning information, and relevant health knowledge of elderly patients with chronic disease.In order to achieve the purpose of active health information service. 2) put forward the improved initiative rules.Because of the particularity of the health information service audience group, the active demand of the health information service is essential, at the same time, the problem of unexpected abnormal signs exists in the practical application, which leads to the inability to provide the accurate health information service.Therefore, this paper studies a variety of active rules, and proposes an improved ECA-Sequence rule which can solve the problem of unexpected signs.Adding the decision of historical sequence to the traditional active rule, according to the length of historical sequence,Combined with hierarchical early warning to solve the problem of providing accurate information service which can not be solved by traditional rules and other improved rules (3) A semi-active rule application model and knowledge ontology building are proposed.In order to improve the efficiency of health information service, improve the rule trigger rate, and meet the hierarchical structure storage of the knowledge base, this paper proposes a semi-active rule application model and establishes the diabetes knowledge ontology database.The establishment of the ontology library can help to improve the rule utilization rate and solve the problem of lack of patients' professional knowledge.
【学位授予单位】：海南大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：R-05;TP391.1

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