An Automatic Approach to Extending the Consumer Health Vocabulary

• 作者: Michal Monselise Jane Greenberg Ou Stella Liang Sonia Pascua Heejun Kim Mat Kelly Joan PBoone Christopher C.Yang
• 来源期刊: 数据与情报科学学报:英文版
• 学科: 工学
• 关键词: Consumer Health Vocabulary Ontological fusion Medical ontologies
• 年，卷（期）: 2021,（1）
• 页码范围: 35-49
• 页数: 15页
• 分类号: TP3

摘要

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(Me SH) ontology into CHV, and further convert CHV from a flat mapping to a hierarchical ontology. The additional relationships and parent terms from Me SH 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 con