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ITAINNOVA at SocialDisNER

Detection of disease mentions in tweets (in Spanish, SMM4H 2022 – Task 10)

Task info

The main source code is organized as follows:

/nb: Notebooks used for data checking

/python: Python source code

  • /data: For corpus transformations needed: offsets to BILOU and BIO tagging scheme

  • /disease_classifier: Specific funcionality developed for the prediction task: transformers-based model and predictor, gazetters, filters and normalization

  • /token_classifier: General Token Classifier implemented over Transformers. It also implements and optimized hyperparameter finetuning connected to Wandb

/script: Command line scripts to launch training and predictions

/test: Unitary tests

Models and files paths have to be set up in the python/config.py script (full paths recommended). Wandb functionality has been deactivated.


Paper

ITAINNOVA at SocialDisNER: A Transformers cocktail for disease identification in social media in Spanish

System architecture

More info at:

Biomedical Text Mining YOUTUBE channel


Contributors

Rosa Montañés - @erremesse

Luis García Garcés - @luisgg98

Irene López Bosque - @irenebosque

Rafael del Hoyo Alonso - @neuralconcept

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