Update README.md

README.md

@@ -4,6 +4,7 @@ language:
 tags:
 - biomedical
 - clinical
+- ehr
 - spanish
 license: apache-2.0
 metrics:
@@ -15,7 +16,7 @@ widget:
 ---
 
 # Biomedical-clinical language model for Spanish
-Biomedical pretrained language model for Spanish. For more details about the corpus, the pretraining and the evaluation, check the official [repository](https://github.com/PlanTL-GOB-ES/lm-biomedical-clinical-es) and read our [preprint](https://arxiv.org/abs/2109.03570) "_Carrino, C. P., Armengol-Estapé, J., Gutiérrez-Fandiño, A., Llop-Palao, J., Pàmies, M., Gonzalez-Agirre, A., & Villegas, M. (2021). Biomedical and Clinical Language Models for Spanish: On the Benefits of Domain-Specific Pretraining in a Mid-Resource Scenario._".
+Biomedical pretrained language model for Spanish. For more details about the corpus, the pretraining and the evaluation, check the official [repository](https://github.com/PlanTL-GOB-ES/lm-biomedical-clinical-es).
 
 ## Tokenization and model pretraining
 This model is a [RoBERTa-based](https://github.com/pytorch/fairseq/tree/master/examples/roberta) model trained on a
@@ -34,21 +35,21 @@ The training corpus is composed of several biomedical corpora in Spanish, collec
   - deduplication of repetitive contents
   - keep the original document boundaries
 
-Then, the biomedical corpora are concatenated and further global deduplication among the biomedical corpora have been applied.
+Then, the biomedical corpora are concatenated and further global deduplication among the biomedical corpora has been applied.
 Eventually, the clinical corpus is concatenated to the cleaned biomedical corpus resulting in a medium-size biomedical-clinical corpus for Spanish composed of more than 1B tokens. The table below shows some basic statistics of the individual cleaned corpora:
 
     
 | Name                                                                                    | No. tokens  | Description                                                                                                                                                                                                                                          |
 |-----------------------------------------------------------------------------------------|-------------|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
-| [Medical crawler](https://zenodo.org/record/4561970)                                    | 745,705,946 | Crawler of more than 3,000 URLs belonging to Spanish biomedical and health domains.                                                                                                                                                                                 |
+| [Medical crawler](https://zenodo.org/record/4561970)                                    | 903,558,13 | Crawler of more than 3,000 URLs belonging to Spanish biomedical and health domains.                                                                                                                                                                                 |
 | Clinical cases misc.                                                                    | 102,855,267 | A miscellany of medical content, essentially clinical cases. Note that a clinical case report is a scientific publication where medical practitioners share patient cases and it is different from a clinical note or document.                                                                                                                                                                                 |
-| Clinical notes/documents                                                                | 91,250,080 | Collection of more than 278K clinical documents, including discharge reports, clinical course notes and X-ray reports, for a total of 91M tokens.                                                                                                                                                                                 |
+| EHR documents                                                                          | 95,267,20 | Collection of more than 278K clinical documents, including discharge reports, clinical course notes and X-ray reports, for a total of 91M tokens.                                                                                                                                                                                 |
 | [Scielo](https://github.com/PlanTL-GOB-ES/SciELO-Spain-Crawler)                        | 60,007,289  | Publications written in Spanish crawled from the Spanish SciELO server in 2017.                                                                                                                                       |
 | [BARR2_background](https://temu.bsc.es/BARR2/downloads/background_set.raw_text.tar.bz2) | 24,516,442  | Biomedical Abbreviation Recognition and Resolution (BARR2) containing Spanish clinical case study sections from a variety of clinical disciplines.                                                                                       |
 | Wikipedia_life_sciences                                                                 | 13,890,501  | Wikipedia articles crawled 04/01/2021 with the [Wikipedia API python library](https://pypi.org/project/Wikipedia-API/) starting from the "Ciencias\_de\_la\_vida" category up to a maximum of 5 subcategories. Multiple links to the same articles are then discarded to avoid repeating content.                                                                                                                                                                    |
 | Patents                                                                                 | 13,463,387  | Google Patent in Medical Domain for Spain (Spanish). The accepted codes (Medical Domain) for Json files of patents are: "A61B", "A61C","A61F", "A61H", "A61K", "A61L","A61M", "A61B", "A61P".                                                        |
 | [EMEA](http://opus.nlpl.eu/download.php?f=EMEA/v3/moses/en-es.txt.zip)                  | 5,377,448   | Spanish-side documents extracted from parallel corpora made out of PDF documents from the European Medicines Agency.                                                                                                                            |
-| [mespen_Medline](https://zenodo.org/record/3562536#.YTt1fH2xXbR)                        | 4,166,077   | Spanish-side articles extracted from a collection of Spanish-English parallel corpus consisting of biomedical scientific literature.  The collection of parallel resources are aggregated from the MedlinePlus source. |
+| [mespen_Medline](https://zenodo.org/record/3562536#.YTt1fH2xXbR)                        | 4,166,077   | Spanish-side articles extracted from a collection of Spanish-English parallel corpus consisting of biomedical scientific literature.  The collection of parallel resources is aggregated from the MedlinePlus source. |
 | PubMed                                                                                  | 1,858,966   | Open-access articles from the PubMed repository crawled in 2017.                                                                                                                                              |
 
 
@@ -79,35 +80,7 @@ The model is ready-to-use only for masked language modelling to perform the Fill
 However, the is intended to be fine-tuned on downstream tasks such as Named Entity Recognition or Text Classification.
 
 ## Cite
-If you use our models, please cite our latest preprint:
-
-```bibtex
-
-@misc{carrino2021biomedical,
-      title={Biomedical and Clinical Language Models for Spanish: On the Benefits of Domain-Specific Pretraining in a Mid-Resource Scenario}, 
-      author={Casimiro Pio Carrino and Jordi Armengol-Estapé and Asier Gutiérrez-Fandiño and Joan Llop-Palao and Marc Pàmies and Aitor Gonzalez-Agirre and Marta Villegas},
-      year={2021},
-      eprint={2109.03570},
-      archivePrefix={arXiv},
-      primaryClass={cs.CL}
-}
-
-```
-
-If you use our Medical Crawler corpus, please cite the preprint:
-
-```bibtex
-
-@misc{carrino2021spanish,
-      title={Spanish Biomedical Crawled Corpus: A Large, Diverse Dataset for Spanish Biomedical Language Models}, 
-      author={Casimiro Pio Carrino and Jordi Armengol-Estapé and Ona de Gibert Bonet and Asier Gutiérrez-Fandiño and Aitor Gonzalez-Agirre and Martin Krallinger and Marta Villegas},
-      year={2021},
-      eprint={2109.07765},
-      archivePrefix={arXiv},
-      primaryClass={cs.CL}
-}
-
-```
+To be announced soon!
 
 ---
 
@@ -171,7 +144,7 @@ This work was funded by the Spanish State Secretariat for Digitalization and Art
 
 The models published in this repository are intended for a generalist purpose and are available to third parties. These models may have bias and/or any other undesirable distortions.
 
-When third  parties, deploy or provide systems and/or services to other parties using any of these models (or using systems based on these models) or become users of the models, they should note that it is their responsibility to mitigate the risks arising from their use and, in any event, to comply with applicable regulations, including regulations regarding the use of artificial intelligence.
+When third parties, deploy or provide systems and/or services to other parties using any of these models (or using systems based on these models) or become users of the models, they should note that it is their responsibility to mitigate the risks arising from their use and, in any event, to comply with applicable regulations, including regulations regarding the use of artificial intelligence.
 
 In no event shall the owner of the models (SEDIA – State Secretariat for digitalization and artificial intelligence) nor the creator (BSC – Barcelona Supercomputing Center) be liable for any results arising from the use made by third parties of these models.