Occupation and occupation holder detection

The task aims to find mentions of occupations in clinical cases and reports of individual patients published in medical journals, as well as determining the person(s) referred to (patient, family member, health professional, someone else).

Publication
Salvador Lima-López, Eulàlia Farré-Maduell, Antonio Miranda-Escalada, Vicent Brivá-Iglesias, Martin Krallinger (2021) NLP applied to occupational health: MEDDOPROF shared task at IberLEF 2021 on automatic recognition, classification and normalization of professions and occupations from medical texts. Procesamiento del Lenguaje Natural, Revista nº 67, septiembre de 2021, pp. 243-256

Task results

System Precision Recall F1 Sort ascending
NLNDE 0.8300 0.7590 0.7930
MUCIC 0.7700 0.7500 0.7640
SMR-NLP 0.8020 0.6990 0.7470
SINAI 0.7750 0.6900 0.7300
Vicomtech NLP-team 0.7100 0.6910 0.7010

If you have published a result better than those on the list, send a message to odesia-comunicacion@lsi.uned.es indicating the result and the DOI of the article, along with a copy of it if it is not published openly.