MultiCardioNER Shared Task Homepage

The MultiCardioNER Track is organized by the Barcelona Supercomputing Center’s NLP for Biomedical Information Analysis group and promoted by Spanish and European projects such as DataTools4Heart, AI4HF, BARITONE and AI4ProfHealth.

Overview of MultiCardioNER task at BioASQ 2024 on Medical Specialty and Language Adaptation of Clinical NER Systems for Spanish, English and Italian. Salvador Lima-López, Eulalia Farre-Maduell, Jan Rodríguez-Miret, Miguel Rodríguez-Ortega, Livia Lilli, Jacopo Lenkowicz, Giovanna Ceroni, Jonathan Kossof, Anoop Shah, Anastasios Nentidis, Anastasia Krithara, Georgios Katsimpras, Georgios Paliouras, Martin Krallinger. Working Notes of CLEF, 2024, pp. 8-27. URL: https://ceur-ws.org/Vol-3740/paper-02.pdf

What is MultiCardioNER?

MultiCardioNER is a shared task and set of resources focused on the multilingual adaptation of clinical NER systems to the cardiology domain.

For more information about the MultiCardioNER task, check the Task Info tab, which includes the Motivation, Subtasks, Schedule, Registration and Submission pages.

To learn more about the MultiCardioNER corpus and how it was annotated, check the Data tab, including the Corpus Description, Annotation Guidelines and Download pages.

MultiCardioNER will be held as part of the BioASQ Workshop in the CLEF 2024 conference. For more information about them, check the Workshop tab.

MultiCardioNER is organized by the Barcelona Supercomputing Center’s NLP for Biomedical Information Analysis group (formerly Text Mining Unit).

Important information

• The BioASQ Proceedings are now available! https://temu.bsc.es/multicardioner/publications/
• The MultiCardioNER complete dataset is out now! https://zenodo.org/doi/10.5281/zenodo.10948354
• The DrugTEMIST Annotation Guidelines are now live! https://zenodo.org/records/11065433
• The task’s evaluation library is now available on GitHub https://github.com/nlp4bia-bsc/multicardioner_evaluation_library

Related resources

At the NLP for Biomedical Information Analysis group (formerly Text Mining Unit), one of our missions is the open publication of datasets to train and benchmark biomedical information extraction, normalization and indexing systems. For that reason, we have released multiple datasets as part of shared tasks over the years. If you are interested in MultiCardioNER, you might want to take a look at some of our resources and competitions about:

• Clinical content extraction: DisTEMIST (diseases), MedProcNER/ProcTEMIST (clinical procedures), SympTEMIST (signs and findings), CANTEMIST (tumour morphology), CodiEsp (coding to ICD), PharmaCoNER (chemicals and proteins), LivingNER (species and humans)
• Sociodemographic content extraction: MEDDOPLACE (locations and more) MEDDOCAN (sensitive data), MEDDOPROF (occupations)
• Information extraction in social media: SocialDisNER (diseases), ProfNER (occupations)
• Linguistic aspects: BARR1 and BARR2 (abbreviation resolution)
• Machine Translation: ClinSpEn (EN<->ES clinical content translation)

Schedule