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A HIERARCHICAL QUANTUM ONTOLOGY METHOD FOR MITIGATING INTEROPERABILITY IN ELECTRONIC PATIENT HEALTH RECORDS

机译:用于缓解电子病历的互操作性的分层量子本体方法

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In the early 1990s, most medical records were a hybrid of paper and electronic data deployed on combinations of mainframe and personal computers (Evans, 2016). The complexity and inadequacies of the mixed paper-electronic medical records was the driver behind the Institute of Medicine's call to shift to a complete electronic medical record (EMR) system (Institute of Medicine, 1997). Advances in computing technology and the Internet during the last two decades has made access to health information online possible. However, as noted by Adler-Milstein (2017). the major technical issue still to be overcome is lack of semantics interoperability. This paper summarizes current approaches to resolving medical terminology differences, and identifies the interoperability errors driving the interoperability problem. The paper then reviews the theory behind quantum ontology primitives, proposes a new method for developing core reference hierarchical quantum ontology primitive trees integrated with ontology learning to mitigate interoperability errors among the primary medical terminologies, and discusses the potential for this method to increase semantics coverages among the medical terminologies.
机译:在1990年代初,大多数医疗记录是纸质数据和电子数据的混合体,部署在大型机和个人计算机的组合上(Evans,2016年)。混合纸质电子病历的复杂性和不足之处是医学研究所呼吁转向完整的电子病历(EMR)系统的推动力(医学研究所,1997年)。在过去的二十年中,计算机技术和互联网的发展使得在线获取健康信息成为可能。但是,正如Adler-Milstein(2017)所指出的那样。尚待克服的主要技术问题是缺乏语义互操作性。本文总结了解决医学术语差异的当前方法,并确定了导致互操作性问题的互操作性错误。然后,本文回顾了量子本体原语背后的理论,提出了一种开发与本体学习相集成的核心参考分层量子本体原语树的新方法,以减轻主要医学术语之间的互操作性错误,并讨论了该方法增加语义覆盖范围的潜力。医学术语。

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