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Methods Inf Med 2013; 52(06): 538-546
DOI: 10.3414/ME13-01-0041
Original Articles
Schattauer GmbH

Biomedical Informatics: We Are What We Publish

P. L. Elkin
1   Department of Biomedical Informatics, University at Buffalo, Buffalo, NY, USA
,
S. H. Brown
2   Department of Veterans Affairs, Washington, DC, USA
3   Department of Biomedical Informatics, Vanderbilt University, Nashville, TN, USA
,
G. Wright
4   Faculty of Health Sciences, Walter Sisulu University, Mthatha, South Africa
› Institutsangaben
Weitere Informationen

Publikationsverlauf

received: 15. April 2013

accepted: 07. August 2013

Publikationsdatum:
20. Januar 2018 (online)

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Summary

Introduction: This article is part of a For-Discussion-Section of Methods of Information in Medicine on “Biomedical Informatics: We are what we publish“. It is introduced by an editorial and followed by a commentary paper with invited comments. In subsequent issues the discussion may continue through letters to the editor.

Objective: Informatics experts have attempted to define the field via consensus projects which has led to consensus statements by both AMIA. and by IMIA. We add to the output of this process the results of a study of the Pubmed publications with abstracts from the field of Biomedical Informatics.

Methods: We took the terms from the AMIA consensus document and the terms from the IMIA definitions of the field of Biomedical Informatics and combined them through human review to create the Health Infor -matics Ontology. We built a terminology server using the Intelligent Natural Language Processor (iNLP). Then we downloaded the entire set of articles in Medline identified by searching the literature by “Medical Informatics” OR “Bioinformatics”. The articles were parsed by the joint AMIA / IMIA terminology and then again using SNOMED CT and for the Bioinformatics they were also parsed using HGNC Ontology.

Results: We identified 153,580 articles using “Medical Informatics” and 20,573 articles using “Bioinformatics”. This resulted in 168,298 unique articles and an overlap of 5,855 articles. Of these 62,244 articles (37%) had titles and abstracts that contained at least one concept from the Health Infor -matics Ontology. SNOMED CT indexing showed that the field interacts with most all clinical fields of medicine.

Conclusions: Further defining the field by what we publish can add value to the consensus driven processes that have been the mainstay of the efforts to date. Next steps should be to extract terms from the literature that are uncovered and create class hierarchies and relationships for this content. We should also examine the high occurring of MeSH terms as markers to define Biomedical Informatics. Greater understanding of the Biomedical Informatics Literature has the potential to lead to improved self-awareness for our field.

Keywords

Medical informatics - bioinformatics - publication record - expert consensus - ontology
 

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