Title

Automated Knowledge Extraction for Decision Model Construction: A Data Mining Approach.

Publication Type

Conference Proceeding Article

Publication Date

1-2003

Abstract

Combinations of Medical Subject Headings (MeSH) and Subheadings in MEDLINE citations may be used to infer relationships among medical concepts. To facilitate clinical decision model construction, we propose an approach to automatically extract semantic relations among medical terms from MEDLINE citations. We use the Apriori association rule mining algorithm to generate the co-occurrences of medical concepts, which are then filtered through a set of predefined semantic templates to instantiate useful relations. From such semantic relations, decision elements and possible relationships among them may be derived for clinical decision model construction. To evaluate the proposed method, we have conducted a case study in colorectal cancer management; preliminary results have shown that useful causal relations and decision alternatives can be extracted.

Discipline

Databases and Information Systems | Data Storage Systems

Research Areas

Data Management and Analytics; Intelligent Systems and Decision Analytics

Publication

American Medical Informatics Association Annual Fall Symposium (AMIA) Proceedings

First Page

758

Last Page

762

ISBN

915138852

Publisher

Bethesda, MD : AMIA

City or Country

Washington DC, USA

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