Risk assessment prediction of hypertension and its associated diseases — An ontology driven model

P. Sherimon, R. Krishnan, P. Vinu, Youseff Takroni
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Abstract

This research paper presents an intelligent system to predict the risk assessment of hypertension in three main related areas like diabetes, cardiovascular problems, and kidney disorders. The system is targeted on patients in Sultanate of Oman. Currently there is no specific system in the domain of hypertension or its associated diseases in the Sultanate. Also currently available medical systems in Oman do not employ an intelligent approach; they are just using database-oriented methodologies. They are not flexible and adaptable to complex requirements and processes and lack intelligence. We propose a system with ontologies as knowledge base (medical knowledge base), patient medical profile to be stored in a semantic way and an inference mechanism to extract data in the decision making process. Ontology is among the most powerful tools to encode medical knowledge formally. Since the knowledge base is constructed through ontology, it can be easily reused and extended in a variety of different problems. The proposed system which is an interactive decision support system (DSS) is a partial replacement of traditional database oriented system which is not capable of finding out patient risk analysis in an intelligent way.
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高血压及其相关疾病的风险评估预测——本体驱动模型
本研究提出了一种智能系统来预测高血压在三个主要相关领域的风险评估,如糖尿病、心血管问题和肾脏疾病。该系统针对的是阿曼苏丹国的患者。目前,在苏丹国的高血压及其相关疾病领域没有专门的系统。此外,阿曼目前可用的医疗系统没有采用智能方法;他们只是使用面向数据库的方法。它们不灵活,不能适应复杂的需求和过程,而且缺乏智能。我们提出了一个以本体为知识库(医学知识库)、以语义方式存储患者医疗档案以及在决策过程中提取数据的推理机制的系统。本体是对医学知识进行形式化编码的最有力工具之一。由于知识库是通过本体构建的,因此可以很容易地在各种不同的问题中进行重用和扩展。本文提出的交互式决策支持系统(DSS)部分取代了传统的面向数据库的系统无法进行智能的患者风险分析。
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