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Convergence Modeling of Heterogeneous Medical Information for Acute Myocardial Infarction

机译:急性心肌梗死异构医学信息的收敛模型

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In recent years, as the big data boom accelerates, the possibility of using personal health and medical data is also growing. However, since most of previous studies have focused on computerizing, storing, and transferring of medical data, it is hard to say that they intelligently use medical data. Particularly, in cases of urgent diseases like acute myocardial infarction (AMI) that prompt diagnosis and treatment is needed, the current hospital information systems are difficult to efficiently provide information. Therefore, in this paper, we propose a convergence modeling method based on semantic relations by analyzing characteristics of medical data for AMI. The proposed method can unify medical data which is separately stored in medical information systems and provide important data as a one record.
机译:近年来,随着大数据繁荣的加速,使用个人健康和医疗数据的可能性也在增加。但是,由于先前的大多数研究都集中在医疗数据的计算机化,存储和传输上,因此很难说它们智能地使用了医疗数据。特别地,在需要迅速诊断和治疗的诸如急性心肌梗塞(AMI)之类的紧急疾病的情况下,当前的医院信息系统难以有效地提供信息。因此,本文通过分析AMI的医学数据特征,提出了一种基于语义关系的收敛建模方法。所提出的方法可以统一存储在医学信息系统中的医学数据,并提供重要数据作为一个记录。

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