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Data Fusion Model from Coupling Ontologies and Clinical Reports to Guide Medical Diagnosis Process

机译:耦合本体和临床报告的数据融合模型指导医学诊断过程

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In this article, we focus on access to data that can help clinicians in the medical diagnostic process before proposing appropriate treatment. With the explosion of medical knowledge, we are interested to structure them into the informations collection step. We propose an ontology resulting from a fusion of several existing and open medical ontologies and terminologies. On the other hand, we exploit real cases of patients to improve the list of signs of each disease. This work leads to a knowledge base (KB) associating all human diseases with their relevant signs. Cases are also stored in the KB. Each disease is described by all the signs observed and verified in all the patients carrying this same disease. The association of sickness and its signs is thus continuously nourished as there are new cases of diagnosis.
机译:在本文中,我们专注于访问能够在提出适当治疗之前帮助临床医生临床医生的数据。 随着医学知识的爆炸,我们有兴趣将它们构建到信息收集步骤中。 我们提出了一种由融合的现有和开放医疗本体和术语产生的本体论。 另一方面,我们利用患者的实际案件改进每种疾病的迹象清单。 这项工作导致知识库(KB)将所有人类疾病与相关迹象相关联。 病例也储存在KB中。 每种疾病都被观察到的所有症状和核查患者患上同样疾病的疾病。 因此,疾病的协会及其迹象是不断滋养的,因为存在新的诊断情况。

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