Pitfalls of ontology in medicine

Bakheet Aldosari, Abdullah Alanazi, Mowafa Househ*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

6 Citations (Scopus)

Abstract

Much research has been done in the last few decades in clinical research, medicine, life sciences, etc. leading to an exponential increase in the generation of data. Managing this vast information not only requires integration of the data, but also a means to analyze, relate, and retrieve it. Ontology, in the field of medicine, describes the concepts of medical terminologies and the relation between them, thus, enabling the sharing of medical knowledge. Ontology-based analyses are associated with a risk that errors in modeling may deteriorate the results' quality. Identifying flawed practices or anomalies in ontologies is a crucial issue to be addressed by researchers. In this paper, we review the negative sides of ontology in the field of medicine. Our study results show that ontologies are perceived as a mere tool to represent medical knowledge, thus relying more on the computer science-based understanding of medical terms. While this approach may be sufficient for data entry systems, in which the users merely need to browse the hierarchy and select relevant terms, it may not suffice the real-world scenario of dealing with complex patient records, which are not only grammatically complex, but also are sometimes documented in many native languages. In conclusion, more research is required in identifying poor practices and anomalies in the development of ontologies by computer scientists within the field of medicine.

Original languageEnglish
Title of host publicationInformatics Empowers Healthcare Transformation
EditorsMowafa S. Househ, John Mantas, Arie Hasman, Parisis Gallos
PublisherIOS Press
Pages15-18
Number of pages4
ISBN (Electronic)9781614997801
DOIs
Publication statusPublished - 2017
Externally publishedYes

Publication series

NameStudies in Health Technology and Informatics
Volume238
ISSN (Print)0926-9630
ISSN (Electronic)1879-8365

Keywords

  • Integration
  • Knowledge
  • Medicine
  • Ontology
  • Pitfalls

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