*MEDDOPROF Shared Task (IberLEF - SEPLN 2021)* *Medical Documents Profession Recognition shared task*
https://temu.bsc.es/meddoprof/ *MEDDOPROF Cup Awards by BSC-Plan TL [€3,000 in prizes]* We’d like to share the CfP of the MEDDOPROF shared task that focuses on professions and occupational status in health data. We are organizing the first shared task focusing on automatic recognition of professions and occupational status (with normalization to standard multilingual terminologies) in medical documents. The relevance of text mining of professions and occupational status encompasses multiple human-interest areas, from health and social services, machine translation in specialized domains, competitive intelligence, human resources, legal NLP, and even gender studies. 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 relationships between disorders and professions may be explained by different factors like increased contact/exposure to hazardous substances, allergens or pathogens; physical injuries due to occupational accidents; higher degrees of social interaction of some professions, or even work-related conditions affecting mental health, to name just a few. Additionally, targeted vaccination plans against emerging diseases also benefit from better characterization of patient professions. Following the success of previously organized shared tasks (i.e., Cantemist, PharmaCoNER and Meddocan), we are now launching the MEDDOPROF shared task as part of the IberLEF 2021 evaluation initiative (co-located with SEPLN 2021), with the following sub-tracks: *MEDDOPROF-NER: *automatic detection of mentions of occupations (profession, employment status and activities). *MEDDOPROF-CLASS: *finding mentions of occupations and classifying them, whether they refer to the patients themselves, their family members or to healthcare professionals. *MEDDOPROF-NORM*: mapping detected occupation mentions to their corresponding concept identifiers from standard multilingual occupation terminologies (ESCO and SNOMED-CT). *Key information:* *MEDDOPROF website:* https://temu.bsc.es/meddoprof/ *Data: *https://doi.org/10.5281/zenodo.4694768 *Annotation guidelines: *https://doi.org/10.5281/zenodo.4694675 *Registration: *https://temu.bsc.es/meddoprof/registration *Google Group for updates*: https://groups.google.com/g/meddoprof-shared-task *Schedule* *Test set release (start of evaluation period): *June 1st, 2021 *End of evaluation period (system submissions): *June 7th, 2021 *Working papers submission*: June 21st, 2021 *Notification of acceptance (peer-review): *June 27th, 2021 *Camera-ready system descriptions*: July 4th, 2021 *IberLEF @ SEPLN 2021: *September 2021 *Publications and IBERLEF/SEPLN2021 workshop* Teams participating in MEDDOPROF will be invited to contribute a system description paper for the IberLEF (SEPLN 2021) Working Notes proceedings, and a short presentation of their approach at the IberLEF 2021 workshop. *Main Organizers* - *Martin Krallinger*, Barcelona Supercomputing Center, Spain - *Eulàlia Farré*, Barcelona Supercomputing Center, Spain - *Salvador Lima*, Barcelona Supercomputing Center, Spain - *Vicent Briva-Iglesias*, D-REAL, Dublin City University, Ireland - *Antonio Miranda-Escalada*, Barcelona Supercomputing Center, Spain *Scientific Committee* - *Sophia Ananadiou*, Department of Computer Science, University of Manchester, UK - *Alec Chapman*, Data Scientist, University of Utah - *Dina Demner-Fushman*, Tenure Track Investigator, Biomedical Informatics Branch, Lister Hill National Center for Biomedical Communications - *Hercules Dalianis*, Professor in Computer and Systems Science, Stockholm University, Sweden - *Hongfang Liu*, Professor of Biomedical Informatics, Mayo Clinic - *Josep Maria Haro Abad*, Institut de Recerca Sant Joan de Déu - *Bradley Malin*, Accenture Professor of Biomedical Informatics, Biostatistics, and Computer Science, Vanderbilt - *Goran Nenadic*, Department of Computer Science, University of Manchester, UK - *Aurélie Névéol*, LIMSI-CNRS, Université Paris-Sud, France - *Øystein Nytrø*, Department of Computer and Information Science, Norges Teknisk-Naturvitenskapelige Universitet (NTNU) - *Carlos Luis Parra Calderón*, Head of Technological Innovation at Virgen del Rocío University Hospital, Institute of Biomedicine of Seville, Spain - *Kirk E. Roberts*, School of Biomedical Informatics, University of Texas Health Science Center - *Francisco Javier Sanz Valero*, Escuela Nacional de Medicina del Trabajo, Instituto de Salud Carlos III, Spain - *Stefan Schulz*, Institute for Medical Informatics, Statistics and Documentation, Medical University of Graz, Austria - *Ashish Tendulkar*, Machine Learning Specialist at Google - *Michelle Turner*, Assistant Research Professor at Barcelona Institute for Global Health, Secretary-Treasurer International Society for Environmental Epidemiology (ISEE) - *Ozlem Uzuner*, George Mason University - *Alfonso Valencia* *Herrera*, Barcelona Supercomputing Center (BSC-CNS), Spain -- *Vicent Briva-Iglesias* PhD Researcher SFI Centre for Research Training in Digitally-Enhanced Reality (D-REAL) School of Applied Language and Intercultural Studies (SALIS) Dublin City University -- __ Séanadh Ríomhphoist/_ Email Disclaimer__ ** Tá an ríomhphost seo agus aon chomhad a sheoltar leis faoi rún agus is lena úsáid ag an seolaí agus sin amháin é. 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