32.1537, Confs: Comp Ling/Online

[The LINGUIST List]

LINGUIST List: Vol-32-1537. Mon May 03 2021. ISSN: 1069 - 4875.

Subject: 32.1537, Confs: Comp Ling/Online

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Date: Mon, 03 May 2021 19:17:38
From: Martin Krallinger [krallinger.martin at gmail.com]
Subject: Medical Documents Profession Recognition shared task at IberLEF/SEPLN2021

 
Medical Documents Profession Recognition shared task at IberLEF/SEPLN2021 
Short Title: MEDDOPROF 

Date: 22-Sep-2021 - 22-Sep-2021 
Location: Virtual, Spain 
Contact: Martin Krallinger 
Contact Email: krallinger.martin at gmail.com 
Meeting URL: https://temu.bsc.es/meddoprof/ 

Linguistic Field(s): Computational Linguistics 

Meeting Description: 

We are organizing the first shared task focusing on automatic recognition of
professions and occupational status (and 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,
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,
just to name a few.
Additionally, targeted vaccination plans also benefit from better
characterization of patient professions. 

Following the success of previously organized shared tasks (i.e. Cantemist,
PharmaCoNER, or 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 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 web: 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 1, 2021 
End of evaluation period (system submissions): June 7, 2021
Working papers submission: June 21, 2021
Notification of acceptance (peer-reviews): June 27, 2021
Camera-ready system descriptions: July 4, 2021
IberLEF @ SEPLN 2021: September 2021

Publications and IBERLEF/SEPLN2021 workshop
Teams participating in MEDDOPROF will be invited to contribute a systems
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
 






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