Outlier concepts auditing methodology for a large family of biomedical ontologies.

Journal: BMC medical informatics and decision making
Published Date: Dec 15, 2020

Abstract

BACKGROUND: Summarization networks are compact summaries of ontologies. The "Big Picture" view offered by summarization networks enables to identify sets of concepts that are more likely to have errors than control concepts. For ontologies that have outgoing lateral relationships, we have developed the "partial-area taxonomy" summarization network. Prior research has identified one kind of outlier concepts, concepts of small partials-areas within partial-area taxonomies. Previously we have shown that the small partial-area technique works successfully for four ontologies (or their hierarchies).

Authors

  • Ling Zheng
    CSSE Department, Monmouth University, West Long Branch, NJ, USA.
  • Hua Min
    Hua Min, Department of Health Administration and Policy, College of Health and Human Services, George Mason University, MS: 1J3, 4400 University Drive, Fairfax, VA 22030-4444, USA, E-mail: hmin3@gmu.edu.
  • Yan Chen
    Department of Respiratory and Critical Care Medicine, Shanghai Pulmonary Hospital, School of Medicine, Tongji University, Shanghai, China.
  • Vipina Keloth
    Department of Computer Science, New Jersey Institute of Technology, Newark, NJ, 07102, USA.
  • James Geller
    Dept of Computer Science, NJIT, Newark, NJ, USA.
  • Yehoshua Perl
    Dept of Computer Science, NJIT, Newark, NJ, USA.
  • George Hripcsak
    Department of Biomedical Informatics, Columbia University, 622 W 168th Street, PH20, New York, NY 10032, USA; Medical Informatics Services, NewYork-Presbyterian Hospital, 622 W 168th Street, PH20, New York, NY 10032, USA. Electronic address: hripcsak@columbia.edu.

Keywords

External Resources

Popular Topics
Recent Journals