xMEN
xMEN is an extensible toolkit for Cross-lingual (x) Medical Entity Normalization. Through its compatibility with the BigBIO (BigScience Biomedical) framework, it can be used out-of-the box to run experiments with many open biomedical datasets. It can also be easily integrated with existing Named Entity Recognition (NER) pipelines.
Links
References
Florian Borchert, Ignacio Llorca, Roland Roller, Bert Arnrich, Matthieu-P. Schapranow xMEN: A Modular Toolkit for Cross-Lingual Medical Entity Normalization. JAMIA Open, Volume 8, Issue 1, ooae147 (2025). [Code] [Hugging Face Models]
Florian Borchert, Ignacio Llorca, Matthieu-P. Schapranow. Improving biomedical entity linking for complex entity mentions with LLM-based text simplification. Database, Volume 2024, 2024, baae067 [Code]
Florian Borchert, Ignacio Llorca, Matthieu-P. Schapranow. HPI-DHC @ BC8 SympTEMIST Track: Detection and Normalization of Symptom Mentions with SpanMarker and xMEN. Proceedings of the BioCreative VIII Challenge and Workshop: Curation and Evaluation in the Era of Generative Models. New Orleans, USA (2023) 🏆 1st place SympTEMIST shared task (entity linking subtrack) [Code]
Florian Borchert, Ignacio Llorca, Matthieu-P. Schapranow Cross-Lingual Candidate Retrieval and Re-ranking for Biomedical Entity Linking. In: Experimental IR Meets Multilinguality, Multimodality, and Interaction. CLEF 2023. Lecture Notes in Computer Science, vol 14163. Springer, Cham 🏆 Best of Labs (BioASQ, CLEF 2022)
Florian Borchert and Matthieu-P. Schapranow. HPI-DHC @ BioASQ DisTEMIST: Spanish Biomedical Entity Linking with Pre-trained Transformers and Cross-lingual Candidate Retrieval. Proceedings of the Working Notes of CLEF 2022 - Conference and Labs of the Evaluation Forum, pp. 244-258. Bologna, Italy. 🏆 1st place DisTEMIST shared task (entity linking subtrack) [Link] [Code]
