Cao Feng, Sun Xingzhi, Wang Xiaoyuan, Li Bo, Li Jing, Pan Yue
IBM Research - China.
Stud Health Technol Inform. 2011;169:699-703.
Since Adverse Drug Event (ADE) has become a leading cause of death around the world, there arises high demand for helping clinicians or patients to identify possible hazards from drug effects. Motivated by this, we present a personalized ADE detection system, with the focus on applying ontology-based knowledge management techniques to enhance ADE detection services. The development of electronic health records makes it possible to automate the personalized ADE detection, i.e., to take patient clinical conditions into account during ADE detection. Specifically, we define the ADE ontology to uniformly manage the ADE knowledge from multiple sources. We take advantage of the rich semantics from the terminology SNOMED-CT and apply it to ADE detection via the semantic query and reasoning.
由于药物不良事件（ADE）已成为全球主要的死亡原因之一，因此对于帮助临床医生或患者识别药物效应可能带来的危害有着很高的需求。受此推动，我们提出了一个个性化的ADE检测系统，重点是应用基于本体的知识管理技术来增强ADE检测服务。电子健康记录的发展使得自动化个性化ADE检测成为可能，即在ADE检测过程中考虑患者的临床状况。具体而言，我们定义了ADE本体，以统一管理来自多个来源的ADE知识。我们利用术语系统医学命名法（SNOMED-CT）的丰富语义，并通过语义查询和推理将其应用于ADE检测。
