CFP- SocialDisNER track: Detection of Disease Mentions in Social Media
(SMM4H Shared Task at COLING2022)
https://temu.bsc.es/socialdisner/ https://mailtrack.io/trace/link/9f641e5f3d28301c54841c67fc044d2c8191cb75?url=https%3A%2F%2Ftemu.bsc.es%2Fsocialdisner%2F&userId=8191969&signature=21ba52f5e6cb738d
Despite the high impact & practical relevance of detecting diseases automatically from social media for a diversity of applications, few manually annotated corpora generated by healthcare practitioners to train/evaluate advanced entity recognition tools are currently available.
Developing disease recognition tools for social media is critical for:
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Real-time disease outbreak surveillance/monitoring -
Characterization of patient-reported symptoms -
Post-market drug safety -
Epidemiology and population health, -
Public opinion mining & sentiment analysis of diseases -
Detection of hate speech/exclusion of sick people -
Prevalence of work-associated diseases
SocialDisNER is the first track focusing on the detection of disease mentions in tweets written in Spanish, with clear adaptation potential not only to English but also other romance languages like Portuguese, French or Italian spoken by over 900 million people worldwide.
For this track the SocialDisNER corpus was generated, a manual collection of tweets enriched for first-hand experiences by patients and their relatives as well as content generated by patient-associations (national, regional, local) as well as healthcare institutions covering all main diseases types including cancer, mental health, chronic and rare diseases among others.
Info:
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Web: https://temu.bsc.es/socialdisner/ https://mailtrack.io/trace/link/c5728f76e1ed5005269d104d71dd52be2f9e1f9d?url=https%3A%2F%2Ftemu.bsc.es%2Fsocialdisner%2F&userId=8191969&signature=fe66f79511f6a35c
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Data: https://mailtrack.io/trace/link/e3e043a9d607f5bf3ca96770c0b03ecdce89a5e1?url=https%3A%2F%2Fdoi.org%2F10.5281%2Fzenodo.6408476&userId=8191969&signature=adbe84aefd4e31f4 https://doi.org/10.5281/zenodo.6359365 https://mailtrack.io/trace/link/c6a15ea9dcb91aa274a210b643b16e779c920331?url=https%3A%2F%2Fdoi.org%2F10.5281%2Fzenodo.6359365&userId=8191969&signature=8a345d6ad7aed260
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Registration: https://temu.bsc.es/socialdisner/registration https://mailtrack.io/trace/link/ce33e75824f6f84ea42b86800565d907cf615647?url=https%3A%2F%2Ftemu.bsc.es%2Fsocialdisner%2Fregistration&userId=8191969&signature=69cf507d58fc6c3a
Schedule
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Development Set Release: June 14th -
Test Set Release: July 11th -
Participant prediction Due: July 15th -
Test set evaluation release: July 25th -
Proceedings paper submission: August 1st -
Camera ready papers: September 1st -
SMM4H workshop @ COLING 2022: October 12-17
Publications and SMM4H (COLING 2022) workshop
Participating teams have the opportunity to submit a short system description paper for the SMM4H proceedings (7th SMM4H Workshop, co-located at COLING 2022). More details are available at https://healthlanguageprocessing.org/smm4h-2022/ https://mailtrack.io/trace/link/66f0903e1381332fb31268e504f6e95bc2d60e97?url=https%3A%2F%2Fhealthlanguageprocessing.org%2Fsmm4h-2022%2F&userId=8191969&signature=1b8fdcd6fab20bbc
SocialDisNER Organizers
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Luis Gascó, Barcelona Supercomputing Center, Spain -
Darryl Estrada, Barcelona Supercomputing Center, Spain -
Eulàlia Farré-Maduell, Barcelona Supercomputing Center, Spain -
Salvador Lima, Barcelona Supercomputing Center, Spain -
Martin Krallinger, Barcelona Supercomputing Center, Spain
Scientific Committee & SMM4H Organizers
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Graciela Gonzalez-Hernandez, Cedars-Sinai Medical Center, USA -
Davy Weissenbacher, University of Pennsylvania, USA -
Arjun Magge, University of Pennsylvania, USA -
Ari Z. Klein, University of Pennsylvania, USA -
Ivan Flores, University of Pennsylvania, USA -
Karen O’Connor, University of Pennsylvania, USA -
Raul Rodriguez-Esteban, Roche Pharmaceuticals, Switzerland -
Lucia Schmidt, Roche Pharmaceuticals, Switzerland -
Juan M. Banda, Georgia State University, USA -
Abeed Sarker, Emory University, USA -
Yuting Guo, Emory University, USA -
Yao Ge, Emory University, USA -
Elena Tutubalina, Insilico Medicine, Hong Kong -
Jey Han Hau, The University of Melbourne (Australia) -
Luca Maria Aiello, IT University of Copenhagen -
Rafael Valencia-Garcia, Universidad de Murcia (Spain) -
Antonio Jimeno Yepes, RMIT University (Australia) -
Carlos Gómez-Rodríguez, Universidad da Coruña (Spain) -
Eugenio Martinez Cámara, Universidad de Granada (Spain) -
Gema Bello Orgaz, Applied Intelligence and Data Analysis Research Group, Universidad Politécnica de Madrid (Spain) -
Juan Antonio Lossio-Ventura, National Institutes of Health (USA) -
Héctor D. Menendez, King's College London (UK) -
Manuel Montes y Gómez, National Institute of Astrophysics, Optics and Electronics (Mexico) -
Helena Gómez Adorno, Universidad Nacional Autónoma de México (Mexico) -
Rodrigo Agerri, IXA Group (HiTZ Centre), University of Basque Country EHU (Spain) -
Miguel A. Alonso, Universidad da Coruña (Spain) -
Ferran Pla, Universidad Politécnica de Valencia (Spain) -
Jose Alberto Benitez-Andrades, Universidad de Leon (Spain)
Darryl Estrada
Full Stack - Web Developer
* Text Mining Unit | Barcelona Supercomputing Center*