Apologies for cross-posting
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*** 2nd 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/3e71c1bed2ad679dff794153eb37d9eefb27b320?url=https%3A%2F%2Ftemu.bsc.es%2Fsocialdisner%2F&userId=8191969&signature=ac4d834347ac613f
Development set, large-scale silver standard, and disease-comoborbility network are now available
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.
As a novelty, we have published a large-scale additional corpus of +85k tweets annotated with diseases, in addition to a disease gazzetter extracted from medical terminologies and a disease-comoborbility network extracted from the large-scale additional corpus.
Info:
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Web: https://temu.bsc.es/socialdisner/ https://mailtrack.io/trace/link/9d2545b93fc6172e6e1cfd016ca9042d4a5e3398?url=https%3A%2F%2Ftemu.bsc.es%2Fsocialdisner%2F&userId=8191969&signature=42a4f66aab04096d
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Data: https://mailtrack.io/trace/link/75e30761b1d2a05960c484153cdc496035092d00?url=https%3A%2F%2Fdoi.org%2F10.5281%2Fzenodo.6408476&userId=8191969&signature=379945c84b0867af https://doi.org/10.5281/zenodo.6359365 https://mailtrack.io/trace/link/a618de145de70b0ada1fd37699b0727391efc5fb?url=https%3A%2F%2Fdoi.org%2F10.5281%2Fzenodo.6359365&userId=8191969&signature=1660038fcf08b59f
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Additional large-scale data: https://zenodo.org/record/6773099 https://mailtrack.io/trace/link/13e20bfcbf66f28252dc074da5459a1d3aed7b25?url=https%3A%2F%2Fzenodo.org%2Frecord%2F6773099&userId=8191969&signature=fa8a67db946a27d5
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Registration: https://temu.bsc.es/socialdisner/registration https://mailtrack.io/trace/link/eef3909672c1e204f68f7e0a3f9b9dddcf6ba744?url=https%3A%2F%2Ftemu.bsc.es%2Fsocialdisner%2Fregistration&userId=8191969&signature=e7331422164f8291
Schedule
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Development Set Release: June 14th -
Additional large-scale corpus with disease annotations: June 28th -
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/183f37b0b6c75261379edcec81c92588f0e28eda?url=https%3A%2F%2Fhealthlanguageprocessing.org%2Fsmm4h-2022%2F&userId=8191969&signature=247e82ee34304ada
SocialDisNER Organizers
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Luis GascĂł, Barcelona Supercomputing Center, Spain -
Darryl Estrada, Barcelona Supercomputing Center, Spain -
Eulà lia 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 OâConnor, University of Pennsylvania, USA -
Raul Rodriguez-Esteban, Roche Pharmaceuticals, Switzerland -
Lucia Schmidt, Roche Pharmaceuticals, Switzerland -
Juan M. Banda, Georgia State University, USA -
çAbeed 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 (Denmark) -
David Camacho, Applied Intelligence and Data Analysis Research Group, Universidad Politécnica de Madrid (Spain) -
Torsten Zesch, Fernuniversitat in Hagen (Germany) -
Eiji ARAMAKI, Nara Institute of Science and Technology (Japan) -
Rafael Valencia-Garcia, Universidad de Murcia (Spain) -
Antonio Jimeno Yepes, RMIT University (Australia) -
Carlos GĂłmez-RodrĂguez, Universidad da Coruña (Spain) -
Anålia Lourenço, Universidade de Vigo (Spain) -
Paloma MartĂnez, Universidad Carlos III de Madrid (Spain) -
Eugenio Martinez CĂĄmara, 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) -
HĂ©ctor D. Menendez, Kingâs College London (UK) -
Manuel Montes y GĂłmez, National Institute of Astrophysics, Optics and Electronics (Mexico) -
Helena GĂłmez Adorno, Universidad Nacional AutĂłnoma de MĂ©xico (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*