Connectionists: Final CFP CANTEMIST shared task: Cancer named entity recognition (IberLEF/SEPLN2020)

[Martin Krallinger]

**** Final CFP 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/ <https://temu.bsc.es/cantemist/>*



Plan TL Award for the Cantemist Track winners



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*.

*The Cantemist sub-tracks:*

*CANTEMIST-NER*: finding mentions of tumor morphology in clinical case
documents.

*CANTEMIST-NORM:* tumor morphology mention recognition and mapping to
concept identifiers from ICD-O-3.

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



*Key information*

Cantemist web: *https://temu.bsc.es/cantemist/
<https://temu.bsc.es/cantemist/>*

Datasets: https://zenodo.org/record/3929739

Registration: *https://temu.bsc.es/cantemist/?p=3956
<https://temu.bsc.es/cantemist/?p=3956>*



*Task motivation*

There is a pressing need to apply NLP to process clinical texts to unlock
critical information that enables better clinical decision-making.
*Understanding
diseases requires the extraction of key entities like diseases, treatments
or symptoms* from textual data. This has become clear from the recent
COVID-19 (SARS-CoV-2, coronavirus disease) pandemic, which showed the
current struggle in processing clinical documents.

Results of systems capable of automatically processing clinical texts are
of interest for the medical user community, researchers, the pharmaceutical
industry as well as patients.

Due to the special relevance of cancer as one of the leading causes of
death and the growing healthcare expenditures for oncological treatments,
the CANTEMIST track tries to promote the development of cancer-relevant NER
resources.



*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 *online evaluation workshop at IberLEF/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*.



*Cantemist awards*

We will grant 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).



*Organizers*

   - *Martin Krallinger*, Text Mining Unit, Barcelona Supercomputing
   Center, Spain
   - *Antonio Miranda*, Text Mining Unit, Barcelona Supercomputing Center,
   Spain
   - *Eulàlia Farré*, Text Mining Unit, Barcelona Supercomputing Center,
   Spain
   - *Jose Antonio Lopez-Martin*, Medical Oncology, Hospital Universitario
   12 de Octubre; Instituto de Investigación Hospital 12 de Octubre (i+12),
   Spain



*Scientific Committee*

   - *Kirk Roberts*, School of Biomedical Informatics, University of Texas
   Health Science Center, USA
   - *Parminder Bhatia*, Amazon Health AI, USA
   - *Irene Spasic*, School of Computer Science & Informatics, co-Director
   of the Data Innovation Research Institute, Cardiff University, UK
   - *Tristan Naumann*, Microsoft Research Healthcare NExT, USA
   - *Carlos Luis Parra Calderón*, Head of Technological Innovation, Virgen
   del Rocío University Hospital, Institute of Biomedicine of Seville, Spain
   - *Ashish Tendulkar*, Google Research
   - *Alfonso Valencia Herrera*, Barcelona Supercomputing Center (BSC-CNS),
   Spain
   - *Hercules Dalianis*, Department of Computer and Systems Sciences,
   Stockholm University, Sweden
   - *Kevin Bretonnel Cohen*, Colorado School of Medicine, USA; LIMSI,
   CNRS, Université Paris-Saclay, France
   - *Karin Verspoor*, School of Computing and Information Systems, Health
   and Biomedical Informatics Centre, University of Melbourne, Australia
   - *Aurélie Névéol*, LIMSI-CNRS, Université Paris-Sud, France
   - *Goran Nenadic*, Department of Computer Science, University of
   Manchester
   - *Antonio Martinez*, Head Pathology, Director National EQAS GCP,
   Spanish Society of Pathology, SEAP-IAP
   - *Zhiyong Lu*, Deputy Director for Literature Search, National Center
   for Biotechnology Information (NCBI)
   - *Ashish Tendulkar*, Machine Learning Architect, Google
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