Paper Info
Title
Automatic annotation of ICD-to-MedDRA mappings with SKOS predicates.
Abstract
Robust alignments between ICD and MedDRA are essential to enable the secondary use of clinical data for pharmacovigilance research. UMLS makes available ICD-to-MedDRA mappings, but they are only poorly specified, which introduces difficulties when exploited in an automatic way. SKOS vocabulary can help achieve quality and machine-processable mappings. We have developed an algorithm based on several simple rules which annotates automatically ICD-to-MedDRA mappings with SKOS predicates. The method was tested and evaluated on a sample of ICD-10-to MedDRA mappings extracted from UMLS. The algorithm demonstrated satisfying performances, especially for skos:exactMatch properties, which suggests that automatic methods can be used to improve the quality of terminology mappings.
Year
DOI
Venue
2014
10.3233/978-1-61499-432-9-1013
Studies in Health Technology and Informatics
Keywords
Field
DocType
ICD-10,MedDRA,SKOS,UMLS,terminology mapping
Data mining,MedDRA,Annotation,Natural language processing,Simple Knowledge Organization System,Artificial intelligence,Predicate (grammar),Medicine
Conference
Volume
ISSN
Citations 
205
0926-9630
0
PageRank 
References 
Authors
0.34
4
4
Name
Order
Citations
PageRank
Gunnar Declerck1115.00
Julien Souvignet273.77
Jean Marie Rodrigues37422.79
Marie-Christine Jaulent437568.72