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Personalizing healthcare services to support decision making in treatment of cancer patients using ontology alignment

机译:个性化医疗服务以支持使用本体比对的癌症患者治疗决策

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The foremost medium of information exchange has been text since ages but with the swift increase in volume of documents it has become a tedious task to organize and retrieve relevant information without the use of text-mining applications. Ontologies are a formal way of representing conceptual knowledge and can be related to text data to assist in this task. There is always a need for accurate interpretation of medical records of cancer patients in deciding intervention plans for proper treatment. However due to the ever changing demand in healthcare services such information sources can be highly variable and may not be suitable for all patients. In this situation the most challenging problem is personalizing healthcare treatment adapted to the patient's medical, social and economic conditions. To manage this problem efficiently the work suggests an ontology alignment model using context aware properties of the system and the patient to facilitate decision making. A patient ontology is mapped to the disease ontology to dynamically transform general treatment options into individual intervention plans most suitable for the patient. The proposed method can be used by medical professionals in recognizing incorrect diagnosis, preventive actions or in identifying co-occurring diseases in the patient.
机译:自古以来,信息交换的最主要媒介就是文本,但是随着文档数量的迅速增加,在不使用文本挖掘应用程序的情况下组织和检索相关信息已成为一项繁琐的任务。本体是表示概念知识的一种形式化方法,可以与文本数据相关以协助完成此任务。在确定适当治疗的干预计划时,始终需要准确解释癌症患者的病历。但是,由于医疗保健服务需求的不断变化,此类信息源可能变化很大,可能并不适合所有患者。在这种情况下,最具挑战性的问题是要根据患者的医疗,社会和经济状况对医疗保健进行个性化设置。为了有效地解决这个问题,这项工作提出了一个本体对齐模型,该模型使用系统和患者的上下文感知属性来促进决策。将患者本体映射到疾病本体,以将一般治疗方案动态转换为最适合患者的个体干预计划。所提出的方法可由医学专业人员用于识别错误的诊断,预防措施或识别患者中的同时发生的疾病。

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