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Journal of Biomedical Informatics
Volume 41, Issue 2, April 2008, Pages 293-317
 
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doi:10.1016/j.jbi.2007.11.001    How to Cite or Link Using DOI (Opens New Window)
Copyright © 2007 Elsevier Inc. All rights reserved.

Comparing and consolidating two heuristic metaschemas

Yan Chena, b, Corresponding Author Contact Information, E-mail The Corresponding Author, Yehoshua Perla, James Gellera, George Hripcsakc and Li Zhangd

aNew Jersey Institute of Technology, Newark, NJ 07102, USA bComputer Information Systems Department, Borough of Manhattan Community College, CUNY, New York, NY 10007, USA cDepartment of Medical Informatics, Columbia University, New York, NY 10032, USA dBusiness and Computer Science Department, College of The Sequoias, Visalia, CA 93277, USA

Received 5 May 2007. 
Available online 17 November 2007.

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Abstract

A metaschema is an Abstraction Network of the UMLS’s Semantic Network (SN) obtained from a connected partition into its collections of semantic types. A metaschema can support comprehension, visualization and navigation of the SN. In this paper, a methodology is presented to evaluate and compare two given metaschemas, based on their structural properties. This methodology was applied to the top-down metaschema and the bottom-up metaschema, derived from two studies involving two groups of UMLS experts. By the Cronbach alpha estimate, the bottom-up metaschema is reliable, while the top-down metaschema is not. An algorithm was designed to yield a consolidated metaschema enjoying the best and avoiding the worst of the two given metaschemas. The consolidation algorithm was applied to the above two metaschemas, The resulting consolidated metaschema has better structural properties than either of the two metaschemas and better supports user orientation visualization, and navigation of the Semantic Network.

Keywords: UMLS; Semantic Network; Abstraction Network; Metaschema; Comparison; Consolidation; Evaluation

Article Outline

1. Introduction
2. Background
2.1. A metaschema of the SN
2.2. Top-down heuristic metaschema
3. Methods
3.1. Design of bottom-up heuristic metaschema
3.1.1. The bottom-up study
3.1.2. Reliability of the experts
3.2. Comparing metaschemas
3.3. Structural properties of metaschemas
3.4. Consolidation
3.4.1. Example
4. Results
4.1. Bottom-up heuristic metaschema
4.2. Results of metaschema comparison
4.3. Results of structural evaluation
4.4. Consolidated metaschema
4.4.1. Step 1
4.4.2. Step 2
4.4.3. Step 3
4.4.4. Step 4
4.4.5. Step 5 for Substance
4.4.6. Step 6 for Chemical
4.4.7. Step 7 for Chemical
4.4.8. Step 8 for Substance
4.4.9. Step 9 for Pharmacologic Substance and Organic Chemical
4.4.10. Step 10 for Chemical
4.4.11. Step 11 for Chemical
4.4.12. Step 12 for Chemical
4.4.13. Step 13 for Chemical
4.4.14. Step 5 for Entity
4.4.15. Step 6 for Entity
4.4.16. Step 7 for Physical Object and Conceptual Entity
4.4.17. Summary of Steps 8–13
4.4.18. Obtaining completely consolidated metaschema MC
4.5. Final consolidated metaschema
5. Discussion
6. Conclusions
Acknowledgements
Glossary
References




















 
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