31.2066, FYI: CFP CANTEMIST-IberLEF2020 Named Entity Recognition

[The LINGUIST List]

LINGUIST List: Vol-31-2066. Wed Jun 24 2020. ISSN: 1069 - 4875.

Subject: 31.2066, FYI: CFP CANTEMIST-IberLEF2020 Named Entity Recognition

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Date: Wed, 24 Jun 2020 05:04:29
From: Martin Krallinger [krallinger.martin at gmail.com]
Subject: CFP CANTEMIST-IberLEF2020 Named Entity Recognition

 
Call for Participation Cantemist:

CANcer TExt Mining Shared Task (IberLEF - SEPLN 2020) ***

Named Entity Recognition of Tumor Morphology Mentions and ICD-O-3 coding track
at SEPLN 2020

https://temu.bsc.es/cantemist/

Plan TL Award for the Cantemist Track winners

Following the success of previous shared tasks we have coordinated in
collaboration with the BioCreative challenges (e.g. ChemDNER, ChemProt),
BioNLP-OST (PharmaCoNER), eHealth CLEF (CodiEsp) or IberLEF2019 (MEDDOCAN) we
are organizing the first shared task specifically focusing on named entity
recognition of a critical type of concept related to cancer, namely tumor
morphology, called CANTEMIST. These previous efforts resulted in high impact
datasets, publications and new tools.  

The Cantemist sub-tracks:

1.CANTEMIST-NER: finding mentions of tumor morphology in oncology cases.

2.CANTEMIST-NORM: recognition and mapping to concept identifiers from ICD-O-3.

3.CANTEMIST-CODING: oncology clinical coding (multi-label classification)
assigning ICD-O-3 codes to clinical case documents.

Key information:

1. Cantemist web, info & detailed description: https://temu.bsc.es/cantemist/

2. Registration for Cantemist: https://temu.bsc.es/cantemist/?p=3956

3. Datasets: https://zenodo.org/record/3878179

Task Motivation:

There is a pressing need to apply natural language processing (NLP) and text
mining technologies to process clinical texts in order to unlock critical
information that enables better clinical decision-making. NLP can facilitate
the use of information from literature and electronic health records in
biomedical data analysis. Understanding diseases requires the extraction of
certain key entities like diseases, treatments or symptoms and their
attributes from textual data, as has become clear from the recent COVID-19
(SARS-CoV-2, coronavirus disease) pandemic, which showed the current struggle
in processing clinical documents written in various languages.

With over 470 million native speakers, there is a worldwide interest in
processing medical texts in Spanish (every 10 minutes, tens of thousands of
EHRs are produced just in Spain). Such technologies also have the potential of
being adapted to handle other languages, like Italian, German, French or even
English.

Results of systems capable of automatically processing clinical texts are not
only of interest for the medical user community or researchers working on
basic and applied health-related disciplines, but are also demanded by the
pharmaceutical industry and ultimately by patients.

Important Dates:

June, 5: Train set and guidelines release
June, 12: First development set release
July, 3: Test and Background set release
Aug, 3: End of the evaluation period
Aug, 14: Paper submission
Sep 1: Camera-ready paper submission
Sep 23-25: SEPLN 2020 Conference

 
Publications and workshop:

There will be an evaluation workshop allocated at SEPLN 2020 where
participating teams can present their systems and results. Moreover,
participating teams will be invited to submit their system description papers
for publication at the SEPLN 2020 Working Notes proceedings. For previous
working notes see: http://ceur-ws.org/Vol-2421/

 
Cantemist awards:

There will be three awards for the top-scoring teams promoted by the Spanish
Plan for the Advancement of Language Technology (Plan TL) and the Barcelona
Supercomputing Center (BSC).

Main Track organizers:

- Martin Krallinger, Barcelona Supercomputing Center, Spain
- Antonio Miranda, Barcelona Supercomputing Center, Spain
- Eulália Farré, Barcelona Supercomputing Center, Spain
- Jose Antonio, Hospital 12 de Octubre, Madrid, Spain
 



Linguistic Field(s): Computational Linguistics

Subject Language(s): Spanish (spa)





 



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