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Bioinformatics Advance Access originally published online on September 18, 2006
Bioinformatics 2006 22(22):2813-2818; doi:10.1093/bioinformatics/btl480
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© 2006 The Author(s)
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commerical License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

ADAM: another database of abbreviations in MEDLINE

Wei Zhou , Vetle I. Torvik and Neil R. Smalheiser *

Department of Psychiatry and Psychiatric Institute, MC912, University of Illinois at Chicago Chicago, IL 60612, USA

*To whom correspondence should be addressed.

Motivation: Abbreviations are an important type of terminology in the biomedical domain. Although several groups have already created databases of biomedical abbreviations, these are either not public, or are not comprehensive, or focus exclusively on acronym-type abbreviations. We have created another abbreviation database, ADAM, which covers commonly used abbreviations and their definitions (or long-forms) within MEDLINE titles and abstracts, including both acronym and non-acronym abbreviations.

Results: A model of recognizing abbreviations and their long-forms from titles and abstracts of MEDLINE (2006 baseline) was employed. After grouping morphological variants, 59 405 abbreviation/long-form pairs were identified. ADAM shows high precision (97.4%) and includes most of the frequently used abbreviations contained in the Unified Medical Language System (UMLS) Lexicon and the Stanford Abbreviation Database. Conversely, one-third of abbreviations in ADAM are novel insofar as they are not included in either database. About 19% of the novel abbreviations are non-acronym-type and these cover at least seven different types of short-form/long-form pairs.

Availability: A free, public query interface to ADAM is available at http://arrowsmith.psych.uic.edu, and the entire database can be downloaded as a text file.

Contact: neils{at}uic.edu

Received on June 14, 2006; revised on September 7, 2006; accepted on September 8, 2006

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V. I. Torvik and N. R. Smalheiser
A quantitative model for linking two disparate sets of articles in MEDLINE
Bioinformatics, July 1, 2007; 23(13): 1658 - 1665.
[Abstract] [Full Text] [PDF]


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