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Published in: BMC Medical Informatics and Decision Making 1/2014

Open Access 01-12-2014 | Research article

Evaluating alignment quality between iconic language and reference terminologies using similarity metrics

Authors: Nicolas Griffon, Gaetan Kerdelhué, Lina F Soualmia, Tayeb Merabti, Julien Grosjean, Jean-Baptiste Lamy, Alain Venot, Catherine Duclos, Stefan J Darmoni

Published in: BMC Medical Informatics and Decision Making | Issue 1/2014

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Abstract

Background

Visualization of Concepts in Medicine (VCM) is a compositional iconic language that aims to ease information retrieval in Electronic Health Records (EHR), clinical guidelines or other medical documents. Using VCM language in medical applications requires alignment with medical reference terminologies. Alignment from Medical Subject Headings (MeSH) thesaurus and International Classification of Diseases – tenth revision (ICD10) to VCM are presented here. This study aim was to evaluate alignment quality between VCM and other terminologies using different measures of inter-alignment agreement before integration in EHR.

Methods

For medical literature retrieval purposes and EHR browsing, the MeSH thesaurus and the ICD10, both organized hierarchically, were aligned to VCM language. Some MeSH to VCM alignments were performed automatically but others were performed manually and validated. ICD10 to VCM alignment was entirely manually performed. Inter-alignment agreement was assessed on ICD10 codes and MeSH descriptors, sharing the same Concept Unique Identifiers in the Unified Medical Language System (UMLS). Three metrics were used to compare two VCM icons: binary comparison, crude Dice Similarity Coefficient (DSC crude ), and semantic Dice Similarity Coefficient (DSC semantic ), based on Lin similarity. An analysis of discrepancies was performed.

Results

MeSH to VCM alignment resulted in 10,783 relations: 1,830 of which were manually performed and 8,953 were automatically inherited. ICD10 to VCM alignment led to 19,852 relations. UMLS gathered 1,887 alignments between ICD10 and MeSH. Only 1,606 of them were used for this study. Inter-alignment agreement using only validated MeSH to VCM alignment was 74.2% [70.5-78.0]CI95%, DSC crude was 0.93 [0.91-0.94]CI95%, and DSC semantic was 0.96 [0.95-0.96]CI95%. Discrepancy analysis revealed that even if two thirds of errors came from the reviewers, UMLS was nevertheless responsible for one third.

Conclusions

This study has shown strong overall inter-alignment agreement between MeSH to VCM and ICD10 to VCM manual alignments. VCM icons have now been integrated into a guideline search engine (http://​www.​cismef.​org) and a health terminologies portal (http://​www.​hetop.​eu).
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Metadata
Title
Evaluating alignment quality between iconic language and reference terminologies using similarity metrics
Authors
Nicolas Griffon
Gaetan Kerdelhué
Lina F Soualmia
Tayeb Merabti
Julien Grosjean
Jean-Baptiste Lamy
Alain Venot
Catherine Duclos
Stefan J Darmoni
Publication date
01-12-2014
Publisher
BioMed Central
Published in
BMC Medical Informatics and Decision Making / Issue 1/2014
Electronic ISSN: 1472-6947
DOI
https://doi.org/10.1186/1472-6947-14-17

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