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ZENODO
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ZENODO
Dataset . 2021
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MEDDOPROF corpus: sample set

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

MEDDOPROF corpus: sample set

Abstract

The MEDDOPROF corpus is a collection of 2000 clinical cases from over 20 different specialties annotated with professions, employment statuses and other work-related activities. It is used for the MEDDOPROF Shared Task on occupations and employment status detection and normalization in Spanish medical documents, which will be celebrated as part of IberLEF 2021. The sample set is composed of 15 clinical cases extracted from the training set from four different specialties: radiology, oncology, psychiatry and occupational health. The files are distributed as follows: - For the subtask 1 (MEDDOPROF-NER), annotations are distributed in Brat standoff format with PROFESION/SITUACION_LABORAL tags only. - For the subtask 2 (MEDDOPROF-CLASS), annotations are distributed in Brat standoff format with PACIENTE/FAMILIAR/SANITARIO/OTROS tags only. - For the subtask 3 (MEDDOPROF-NORM), annotations are distributed in a tab-separated file (TSV) with a code column that includes the mapping of entities to ESCO and SNOMED-CT. For further information, please visit https://temu.bsc.es/meddoprof/ or email us at encargo-pln-life@bsc.es

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Keywords

Professions, normalization, meddoprof, NER, clinical NLP, clinical cases, Occupations, NLP

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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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