Relating Complexity and Error Rates of Ontology Concepts. More Complex NCIt Concepts Have More Errors.

Journal: Methods of information in medicine

Published Date: May 18, 2017

Abstract

OBJECTIVES: Ontologies are knowledge structures that lend support to many health-information systems. A study is carried out to assess the quality of ontological concepts based on a measure of their complexity. The results show a relation between complexity of concepts and error rates of concepts.

Authors

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.
Ling Zheng

CSSE Department, Monmouth University, West Long Branch, NJ, USA.
Yehoshua Perl

Dept of Computer Science, NJIT, Newark, NJ, USA.
Michael Halper

New Jersey Institute of Technology, Newark, NJ.
Sherri De Coronado
Christopher Ochs

New Jersey Institute of Technology, Newark, NJ.

Keywords

Biological Ontologies Comprehension Computer Simulation Humans Meaningful Use Models, Statistical National Cancer Institute (U.S.) Natural Language Processing Neoplasms Quality Assurance, Health Care United States Vocabulary, Controlled

External Resources

View on PubMed Access via DOI PubMed (28244549)

Relating Complexity and Error Rates of Ontology Concepts. More Complex NCIt Concepts Have More Errors.

Abstract

Authors

Keywords

External Resources

Popular Topics

Recent Journals