Open call to researchers and healthcare professionals to explore automatic detection of occupations and employment status in Spanish medical documents

14 May 2021

Funded by the Plan de Impulso de las Tecnologías del Lenguaje (PlanTL), proposals can be submitted until June 1st, 2021.

The competition called MEDDOPROF (Medical Documents Profession Recognition shared task) invites researchers and experts from the healthcare industry to explore the automatic detection of occupations and employment status in Spanish medical documents. Organized by the Barcelona Supercomputing Center, within the frame of the Plan for the Boosting of Language Technologies (Plan TL) of the Spanish Secretariat for Digitalization and Artificial Intelligence, MEDDOPROF aims to contains a comprehensive range of mentions of occupations and employment status including a wide range of specialties: infectious diseases (including Covid-19 case reports), cardiology, neurology, oncology, psychiatry, urology, internal medicine, emergency and intensive care medicine, radiology, tropical medicine and dermatology. Interested teams are able to register until 1 June 2021.

The relevance of text mining of professions and occupational status encompasses multiple human-interest areas, from health and social services, competitive intelligence, human resources, legal NLP and even gender studies. Eulalia Farré, BSC researcher within the Text mining unit of BSC’s Life Science department, thinks that “the need to implement advanced NER systems to detect professions in medical texts has been underscored by the current pandemic, in which the risk of selected occupational groups has resulted in higher mortality and morbidity for these segments of the population.”

The MEDDOPROF shared task is part of the Iberian Languages Evaluation Forum (IberLEF 2021) co-located with the SEPLN 2021 conference, which will be held in September 2021 in Spain. BSC researchers organize this task in collaboration with researchers from the Dublin City University, Ireland. The three top teams will receive prizes , and results will be published on an open source repository available to other community members.

For more information, visit the dedicated website here: or please contact:



Caption: Overview of the MEDDOPROF Shared Task