• Farré-Maduell, Eulàlia
• Miranda-Escalada, Antonio
• Lima-López, Salvador
• Krallinger, Martin
• Briva-Iglesias, Vicent

Abstract

The MEDDOPROF Shared Task tackles the detection of occupations and employment statuses in clinical cases in Spanish from different specialties. Systems capable of automatically processing clinical texts are of interest to the medical community, social workers, researchers, the pharmaceutical industry, computer engineers, AI developers, policy makers, citizen’s associations and patients. Additionally, other NLP tasks (such as anonymization) can also benefit from this type of data. MEDDOPROF has three different sub-tasks: 1) MEDDOPROF-NER: Participants must find the beginning and end of occupation mentions and classify them as PROFESION (PROFESSION) or SITUACION_LABORAL (WORKING_STATUS) 2) MEDDOPROF-CLASS: Participants must find the beginning and end of occupation mentions and classify them according to their referent (PACIENTE [patient], FAMILIAR [family member], SANITARIO [health professional] or OTRO [other]). 3) MEDDOPROF-NORM: Participants must find the beginning and end of occupation mentions and normalize them according to a reference codes list.MEDDOPROF is part of the IberLEF 2021 workshop, which is co-located with the SEPLN 2021 conference. For further information, please visit https://temu.bsc.es/meddoprof/ or email us at encargo-pln-life@bsc.es MEDDOPROF is promoted by the Plan de Impulso de las Tecnologías del Lenguaje de la Agenda Digital (Plan TL). UPDATE 22/04/21: A new version of the training data has been uploaded after detecting some minor errors in some of the annotations. Training data for Task 3 (MEDDOPROF-NORM) has also been added. Please make sure to download the latest version! Resources: - Web - Annotation Guidelines

Topics

• impedance spectroscopy
• laser absorption spectroscopy