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, 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, Roland Roller, Bert Arnrich, Matthieu-P. Schapranow xMEN: A Modular Toolkit for Cross-Lingual Medical Entity Normalization. arXiv preprint arXiv:2310.11275 (2023). [Code] [Hugging Face Models]
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]
