Journal of Data and Information Science

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An Automatic Approach to Extending the Consumer Health Vocabulary

Michal Monselise, Jane Greenberg, Ou Stella Liang, Sonia Pascua, Heejun Kim, Mat Kelly, Joan P. Boone, Christopher C. Yang   

  1. Drexel University, Philadelphia, PA, USA
  • Received:2020-03-11 Revised:2020-07-16 Accepted:2020-08-27
  • Contact: † Michal Monselise E-mail:michal.monselise@gmail.com

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.

Key words: Consumer Health Vocabulary, Ontological fusion, Medical ontologies