Improving the Mapping between MedDRA and SNOMED CT View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2011

AUTHORS

Fleur Mougin , Marie Dupuch , Natalia Grabar

ABSTRACT

MedDRA is exploited for the indexing of pharmacovigilance spontaneous reports. But since spontaneous reports cover only a small proportion of the existing adverse drug reactions, the exploration of clinical reports is seriously considered. Through the UMLS, the current mapping between MedDRA and SNOMED CT, this last being used for indexing clinical data in many countries, is only 42%. In this work, we propose to improve this mapping through an automatic lexical-based approach. We obtained 308 direct mappings of a MedDRA term to a SNOMED CT concept. After segmenting MedDRA terms, we identified 535 full mappings associating a MedDRA term with one or more SNOMED CT concepts. The direct approach resulted in 199 (64.6%) correct mappings while through segmentation this number raises to 423 (79.1%). On the whole, our method provided interesting and useful results. More... »

PAGES

220-224

References to SciGraph publications

Book

TITLE

Artificial Intelligence in Medicine

ISBN

978-3-642-22217-7
978-3-642-22218-4

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-3-642-22218-4_27

DOI

http://dx.doi.org/10.1007/978-3-642-22218-4_27

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1043957792


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