ClinIDMap: Towards a Clinical IDs Mapping for Data Interoperability

Elena Zotova, Montse Cuadros, German Rigau


Abstract
This paper presents ClinIDMap, a tool for mapping identifiers between clinical ontologies and lexical resources. ClinIDMap interlinks identifiers from UMLS, SMOMED-CT, ICD-10 and the corresponding Wikipedia articles for concepts from the UMLS Metathesaurus. Our main goal is to provide semantic interoperability across the clinical concepts from various knowledge bases. As a side effect, the mapping enriches already annotated corpora in multiple languages with new labels. For instance, spans manually annotated with IDs from UMLS can be annotated with Semantic Types and Groups, and its corresponding SNOMED CT and ICD-10 IDs. We also experiment with sequence labelling models for detecting Diagnosis and Procedures concepts and for detecting UMLS Semantic Groups trained on Spanish, English, and bilingual corpora obtained with the new mapping procedure. The ClinIDMap tool is publicly available.
Anthology ID:
2022.lrec-1.390
Volume:
Proceedings of the Thirteenth Language Resources and Evaluation Conference
Month:
June
Year:
2022
Address:
Marseille, France
Editors:
Nicoletta Calzolari, Frédéric Béchet, Philippe Blache, Khalid Choukri, Christopher Cieri, Thierry Declerck, Sara Goggi, Hitoshi Isahara, Bente Maegaard, Joseph Mariani, Hélène Mazo, Jan Odijk, Stelios Piperidis
Venue:
LREC
SIG:
Publisher:
European Language Resources Association
Note:
Pages:
3661–3669
Language:
URL:
https://aclanthology.org/2022.lrec-1.390
DOI:
Bibkey:
Cite (ACL):
Elena Zotova, Montse Cuadros, and German Rigau. 2022. ClinIDMap: Towards a Clinical IDs Mapping for Data Interoperability. In Proceedings of the Thirteenth Language Resources and Evaluation Conference, pages 3661–3669, Marseille, France. European Language Resources Association.
Cite (Informal):
ClinIDMap: Towards a Clinical IDs Mapping for Data Interoperability (Zotova et al., LREC 2022)
Copy Citation:
PDF:
https://aclanthology.org/2022.lrec-1.390.pdf
Code
 vicomtech/clinidmap
Data
MedMentions