Treffer: Context-based ontology building support in clinical domains using formal concept analysis

Title:
Context-based ontology building support in clinical domains using formal concept analysis
Authors:
GUOQIAN JIANG, OGASAWARA, Katsuhiko, ENDOH, Akira, SAKURAI, Tsunetaro
Source:
International journal of medical informatics. 71(1):71-81
Publisher Information:
Shannon: Elsevier, 2003.
Publication Year:
2003
Physical Description:
print, 47 ref
Original Material:
INIST-CNRS
Subject Terms:
Biomedical engineering, Génie biomédical, Computer science, Informatique, Sciences biologiques et medicales, Biological and medical sciences, Sciences medicales, Medical sciences, Formal concept analysis, Information retrieval, Knowledge acquisition, Knowledge representation, Medical records, Natural language processing
Document Type:
Fachzeitschrift Article
File Description:
text
Language:
English
Author Affiliations:
Department of Medical Informatics, Hokkaido University Graduate School of Medicine, North 15, West 7, Kita-ku, Sapporo 060-8638, Japan
Department of Radiological Technology, Hokkaido University College of Medical Technology, Sapporo, Japan
ISSN:
1386-5056
Access URL:
http://pascal-francis.inist.fr/vibad/index.php?action=search&terms=15040338
Rights:
Copyright 2003 INIST-CNRS
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
Notes:
Generalities in medical sciences
Accession Number:
edscal.15040338
Database:
PASCAL Archive

Weitere Informationen

Objective: Ontology in clinical domains is becoming a core research field in the realm of medical informatics. The objective of this study is to explore the potential role of formal concept analysis (FCA) in a context-based ontology building support in a clinical domain (e.g. cardiovascular medicine here). Methodology: We developed an ontology building support system that integrated an FCA module with a natural language processing (NLP) module. The user interface of the system was developed as a Protégé-2000 JAVA tab plug-in. A collection of 368 textual discharge summaries and a standard dictionary of Japanese diagnostic terms (MEDIS ver2.0) were used as the main knowledge sources. A preliminary evaluation was taken to show the usefulness of the system. Results: Stability was shown on the MEDIS-based medical concept extraction with high precision. 73±14% (mean±S.D.) of the compound medical phrases extracted were sufficiently meaningful to form a medical concept from a clinical perspective. Also, 57.7% of attribute implication pairs (i.e. medical concept pairs) extracted were identified as positive from a clinical perspective. Conclusion: Under the framework of our ontology building support system using FCA, the clinical experts could reach a mass of both linguistic information and context-based knowledge that was demonstrated as useful to support their ontology building tasks.