An Automatic Approach to Extending the Consumer Health Vocabulary

Michal Monselise, J. Greenberg, Ou Stella Liang, Sonia M. Pascua, Heejun Kim, Mat Kelly, Joan Boone, Christopher C. Yang
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引用次数: 3

Abstract

Abstract Purpose Given the ubiquitous presence of the internet in our lives, many individuals turn to the web for medical information. A challenge here is that many laypersons (as “consumers”) do not use professional terms found in the medical nomenclature when describing their conditions and searching the internet. The Consumer Health Vocabulary (CHV) ontology, initially developed in 2007, aimed to bridge this gap, although updates have been limited over the last decade. The purpose of this research is to implement a means of automatically creating a hierarchical consumer health vocabulary. This overall purpose is improving consumers’ ability to search for medical conditions and symptoms with an enhanced CHV and improving the search capabilities of our searching and indexing tool HIVE (Helping Interdisciplinary Vocabulary Engineering). Design/methodology/approach The research design uses ontological fusion, an approach for automatically extracting and integrating the Medical Subject Headings (MeSH) ontology into CHV, and further convert CHV from a flat mapping to a hierarchical ontology. The additional relationships and parent terms from MeSH allow us to uncover relationships between existing terms in the CHV ontology as well. The research design also included improving the search capabilities of HIVE identifying alternate relationships and consolidating them to a single entry. Findings The key findings are an improved CHV with a hierarchical structure that enables consumers to search through the ontology and uncover more relationships. Research limitations There are some cases where the improved search results in HIVE return terms that are related but not completely synonymous. We present an example and discuss the implications of this result. Practical implications This research makes available an updated and richer CHV ontology using the HIVE tool. Consumers may use this tool to search consumer terminology for medical conditions and symptoms. The HIVE tool will return results about the medical term linked with the consumer term as well as the hierarchy of other medical terms connected to the term. Originality/value This is a first attempt in over a decade to improve and enhance the CHV ontology with current terminology and the first research effort to convert CHV's original flat ontology structure to a hierarchical structure. This research also enhances the HIVE infrastructure and provides consumers with a simple, efficient mechanism for searching the CHV ontology and providing meaningful data to consumers.
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一种自动扩展消费者健康词汇的方法
鉴于互联网在我们生活中无处不在,许多人转向网络获取医疗信息。这里的一个挑战是,许多外行(作为“消费者”)在描述他们的病情和搜索互联网时不使用医学术语。消费者健康词汇(CHV)本体最初于2007年开发,旨在弥补这一差距,尽管在过去十年中更新有限。本研究的目的是实现一种自动创建分层消费者健康词汇表的方法。这一总体目的是提高消费者使用增强的CHV搜索医疗条件和症状的能力,并提高我们的搜索和索引工具HIVE(帮助跨学科词汇工程)的搜索能力。设计/方法/方法本研究设计采用本体融合的方法,将医学主题词(MeSH)本体自动提取并集成到CHV中,进而将CHV从平面映射转化为层次本体。来自MeSH的附加关系和父术语也允许我们发现CHV本体中现有术语之间的关系。研究设计还包括提高HIVE识别替代关系的搜索能力,并将它们整合到单个条目中。主要发现是改进的CHV具有层次结构,使消费者能够在本体中搜索并发现更多关系。在某些情况下,HIVE中改进的搜索结果返回相关但不完全同义的术语。我们给出了一个例子,并讨论了这一结果的含义。本研究利用HIVE工具提供了更新和更丰富的CHV本体。消费者可以使用此工具搜索医疗条件和症状的消费者术语。HIVE工具将返回与消费者术语相关的医学术语的结果,以及与该术语相关的其他医学术语的层次结构。这是十多年来第一次尝试用现有术语对CHV本体进行改进和增强,也是第一次将CHV原有的平面本体结构转化为层次结构的研究。本研究还增强了HIVE基础架构,为消费者提供了一种简单、高效的CHV本体搜索机制,为消费者提供有意义的数据。
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