Towards the integration of W ord N et into C lin IDM ap (2023)

Abstract: This paper presents the integration of WordNet knowledge resource into ClinIDMap tool, which aims to map identifiers between clinical ontologies and lexical resources. ClinIDMap interlinks identifiers from UMLS, SMOMED-CT, ICD-10 and the corresponding Wikidata and Wikipedia articles for concepts from the UMLS Metathesaurus. The main goal of the tool is to provide semantic interoperability across the clinical concepts from various knowledge bases. As a side effect, the mapping enriches already annotated medical corpora in multiple languages with new labels. In this new release, we add WordNet 3.0 and 3.1 synsets using the available mappings through Wikidata. Thanks to cross-lingual links in MCR we also include the corresponding synsets in other languages and also, extend further ClinIDMap with different domain information. Finally, the final resource helps in the task of enriching of already annotated clinical corpora with additional semantic annotations.

## introduction the main goal of the clinidmap mapping tool @xcite is to align different types of clinical identifiers (ids, codes) from different knowledge bases (kb) such as umls @xcite ), icd-10 (world health organization (who), 2004), snomed-ct @xcite and others. the alignment uses the actual ids of the kbs from the official mapping resources developed by the authors of snomed-ct and umls. the alignment allows to enrich manually annotated corpora with extra clinical codes and to obtain multilingual inter-operable corpora annotated with various coding systems. for instance, if we have a corpus annotated in umls codes we can map each code to icd-10-cm and icd-10-psc codes in order to derive automatically a new version of the corpus with icd-10 annotations. and vise versa, corpus annotated with icd-10 codes can be used to derive automatically new corpora annotated with umls codes, semantic types or groups. moreover, clinidmap enriches the annotated concepts with multilingual terms and descriptions of its available wikidata and wikipedia articles, allowing to expand brief code descriptions to detailed information in multiple languages. now, we introduce the functionality of mapping those clinical concepts to wordnet @xcite . wordnet (wn) is a widely used lexical knowledge resource, which contains information about lexical relations, such as synonyny and super-subordinate relation (hyperonymy, hyponymy). in addition, wordnet is used as a backbone of many other lexical resources. the alignment allows us to enrich manually annotated corpora with extra clinical codes and to obtain multilingual inter-operable cor-pora annotated with various coding systems. for instance, if we have a corpus annotated in umls codes we can map each code to icd-10-cm and icd-10-psc codes in order to derive automatically a new version of the corpus. and vise versa, a corpus annotated with icd-10 codes can be used to derive automatically new corpora annotated with umls codes, semantic types or groups. thus, this paper focuses on two tasks: (1) extending clinidmap to include wordnet information, and (2) annotating automatically clinical corpora with new labels related to information associated to wordnet. concretely, we present the integration of wordnet mapping with clinical identifiers such as umls, snomed-ct, icd-10, mesh a for spanish, english and other languages. using this tool, we derive multiple datasets annotated with different coding systems on the base of existing annotated corpora. the previous version of the tool is described in detail in @xcite and the tool is publicly available foot_0 . for instance, a spanish sentence from e3c corpus @xcite the code c0031154 corresponding to the spanish term peritonitis can be mapped to the snomed ct code 235983003, to the icd-10-cm code k65, to the corresponding wikipedia articles in 48 languages, to synset 14376092-n in wordnet 3.1. and synset 14352687-n in wordnet 3.0. the paper is organized as follows. section 2 describes previous attempts of mapping clinical codes and also using wordnet in the clinical domain; section 3 is dedicated to the databases used to develop clinidmap-clinical ontologies, mapping schema and general purpose lexical resources; in section 4 we describe (1) the method of aligning wordnet synsets to clinical codes, wordnet domains and wordnets in different languages (subsection 4.1) and (2) semi-automatic method of annotating of the clinical corpora (subsection 4.2).finally, section 5 concludes the paper and presents the future work. ## background this section describes the resources and databases used to build clinidmap. it includes a brief information about the clinical and general knowledge bases used and the resources exploited for mapping the different codes. ## conclusions in this paper we present an extension of clinidmap now integrating wordnet synsets in different languages and its domain information. we also use the new medical resource to provide different prespectives to the annotated data. as a future work we