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Abstract：
Ontologies serve as comprehensive frameworks for organizing domain-specific knowledge, offering significant benefits for managing clinical data. This study presents the development of the Fall Risk Management Ontology (FRMO), designed to enhance clinical text mining, facilitate integration and interoperability between disparate data sources, and streamline clinical data analysis. By representing major entities within the fall risk management domain, the FRMO supports the unification of clinical language and decision-making processes, ultimately contributing to the prevention of falls among older adults. We used Ontology Web Language (OWL) to build the FRMO in Protégé. Of the seven steps of the Stanford approach, six steps were utilized in the development of the FRMO: (1) defining the domain and scope of the ontology, (2) reusing existing ontologies when possible, (3) enumerating ontology terms, (4) specifying the classes and their hierarchy, (5) defining the properties of the classes, and (6) defining the facets of the properties. We evaluated the FRMO using four main criteria: consistency, completeness, accuracy, and clarity. The developed ontology comprises 890 classes arranged in a hierarchical structure, including six top-level classes with a total of 43 object properties and 28 data properties. FRMO is the first comprehensively described semantic ontology for fall risk management. Healthcare providers can use the ontology as the basis of clinical decision technology for managing falls among older adults.
摘要：
本体作为组织特定领域知识的综合框架，为管理临床数据提供了显著的好处。本研究介绍了秋季风险管理本体论(FRMO)的发展，旨在增强临床文本挖掘，促进不同数据源之间的集成和互操作性，和临床精简数据分析。通过代表秋季风险管理领域的主要实体，FRMO支持临床语言和决策过程的统一，最终有助于预防老年人跌倒。我们使用本体Web语言（OWL）在Protégé中构建FRMO。斯坦福方法的七个步骤中，在FRMO的开发中使用了六个步骤：(1)定义本体的领域和范围，(2)在可能的情况下重用现有的本体，(3)枚举本体术语，（4）指定类及其层次结构，（5）定义类的属性，和（6）定义属性的方面。我们使用四个主要标准评估FRMO：一致性，完整性，准确度,和清晰度。开发的本体包括按层次结构排列的890个类，包括六个顶级类，总共43个对象属性和28个数据属性。FRMO是第一个全面描述跌倒风险管理的语义本体。医疗保健提供者可以使用本体作为临床决策技术的基础，以管理老年人的跌倒。
