基于本体的以患者为中心的云系统远程医疗安全自诊断知识表示

Keke Gai, Meikang Qiu, Saravanan Jayaraman, Lixin Tao
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引用次数: 24

摘要

在远程保健中实施云计算,为改善保健服务和积极的保健方法,如以病人为中心的远程保健(PCT)带来了巨大好处。应用云系统使医疗保健用户能够从多个基于云的平台或来源获取医疗信息。不同的服务部署可以满足不同客户的需求。在线自我诊断(OSD)作为云上流行的信息共享方式之一,已经在各个医疗领域广泛应用于推荐药物或治疗方案。然而,由于缺乏专业的药理学知识,使用者在执行OSD时存在很大的风险。本文针对这一问题,提出了一种基于本体的医学知识表示方法,以警示潜在风险。该机制被命名为基于安全本体的自我诊断模型(SOS),该模型旨在生成药物治疗或药物不相容的知识,以避免诊断的不当行为。在该模型的基础上,本文提出了基于语义模式的结构级匹配算法,即命题可满足性匹配算法(PSMA)。我们的实验证明了我们提出的机制的可行性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Ontology-Based Knowledge Representation for Secure Self-Diagnosis in Patient-Centered Teleheath with Cloud Systems
The implementation of cloud computing in tele-health has enabled enormous benefits of improving health-care services as well as active health approaches, such as Patient-Centered Telehealth (PCT). Applying cloud systems enables healthcare users to obtain medical information from multiple cloud-based platforms or sources. Various service deployments meet different customers' needs. As one of the popular information sharing manners on clouds, Online Self-Diagnosis (OSD) has been widely implemented for recommending medicines or treatment plans in the varied medical fields. However, there is a great risk for users when executing OSD since lack of professional pharmacological knowledge. This paper concentrates on this issue and proposes an ontology-based approach representing the medical knowledge for alarming potential risks. The proposed mechanism is named Secure Ontology-based Self-diagnosis (SOS) Model that is designed to generate knowledge of medical treatments or incompatibility of medicines to avoid improper behaviors of diagnoses. Based on the proposed model, our algorithm uses structure-level technique applying semantic schemas, which is Propositional Satisfiability Matching Algorithm (PSMA). Our experiment has proved the feasibility of our proposed mechanism.
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