Translating UMLS Concepts to Improve Medical Entity Linking in French: A SapBERT-Based Approach

Medical Entity Linking (MEL) refers to the task of automatically detecting and codifying medical concepts, which is an important preprocessing step for exploiting unstructured medical reports. SapBERT is an efficient MEL method for the English language. Unfortunately, its cross-language counterpart underperforms in French due to the lack of training data. To address this limitation, this paper explores the possibility of training SapBERT on machine-generated French translations of the UMLS Metathesaurus. Evaluation on the QuaeroFrenchMed benchmark demonstrates that this approach outperforms Cross-lingual SapBERT for SNOMED-CT MEL on the QuaeroFrenchMed benchmark.