Expressing Biomedical Ontologies in Natural Language for Expert Evaluation.

Journal: Studies in health technology and informatics
Published Date:

Abstract

We report on a study of our custom Hootation software for the purposes of assessing its ability to produce clear and accurate natural language phrases from axioms embedded in three biomedical ontologies. Using multiple domain experts and three discrete rating scales, we evaluated the tool on clarity of the natural language produced, fidelity of the natural language produced from the ontology to the axiom, and the fidelity of the domain knowledge represented by the axioms. Results show that Hootation provided relatively clear natural language equivalents for a select set of OWL axioms, although the clarity of statements hinges on the accuracy and representation of axioms in the ontology.

Authors

  • Muhammad Amith
    University of Texas Health Science Center.
  • Frank J Manion
    School of Biomedical Informatics, University of Texas Health Science Center, Houston, Texas, United States.
  • Marcelline R Harris
    Division of Systems Leadership and Effectiveness Science, University of Michigan School of Nursing, Ann Arbor, MI, 48109, USA.
  • Yaoyun Zhang
    Alibaba Damo Academy, 969 West Wen Yi Road, Yu Hang District, Hangzhou, Zhejiang, China.
  • Hua Xu
    Department of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
  • Cui Tao
    The University of Texas Health Science Center at Houston, USA.