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Advances in Dental Research
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Adv Dent Res 17:115-120, December, 2003
© 2003 SAGE Publications

Retrieval and Classification of Dental Research Articles

Presented at "Dental Informatics & Dental Research: Making the Connection", a conference held in, Bethesda, MD, USA, June 12–13, 2003, sponsored by the University of Pittsburgh Center for Dental Informatics and supported in part by award 1R13DE014611-01 from the National Institute of Dental and Craniofacial Research/National Library of Medicine.

W.C. Bartling1,*, T.K. Schleyer2 and S. Visweswaran1

1 Center for Biomedical Informatics, University of Pittsburgh, Pittsburgh, PA;
2 Center for Dental Informatics, School of Dental Medicine, University of Pittsburgh, Pittsburgh, PA;

Correspondence: * corresponding author, wcb{at}cbmi.upmc.edu

Successful retrieval of a corpus of literature on a broad topic can be difficult. This study demonstrates a method to retrieve the dental and craniofacial research literature. We explored MeSH manually for dental or craniofacial indexing terms. MEDLINE was searched using these terms, and a random sample of references was extracted from the resulting set. Sixteen dental research experts categorized these articles, reading only the title and abstract, as either: (1) dental research, (2) dental non-research, (3) non-dental, or (4) not sure. Identify Patient Sets (IPS), a probabilistic text classifier, created models, based on the presence or absence of words or UMLS phrases, that distinguished dental research articles from all others. These models were applied to a test set with different inputs for each article: (1) title and abstract only, (2) MeSH terms only, or (3) both. By title and abstract only, IPS correctly classified 64% of all dental research articles present in the test set. The percentage of correctly classified dental research articles in this retrieved set was 71%. MeSH term inclusion decreased performance. Computer programs that use text input to categorize articles may aid in retrieval of a broad corpus of literature better than indexing terms or key words alone.

Key Words: Dental research • information retrieval • inter-rater agreement • MEDLINE • MeSH • data mining • text classification

Advances in Dental Research, Vol. 17, No. 1, 115-120 (2003)
DOI: 10.1177/154407370301700126
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