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@@ -37,6 +37,9 @@ results = [{'token': input_tokens[idx],
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  ```
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  It is perhaps good to note that we assume the [Inside-Outside-Beginning](https://en.wikipedia.org/wiki/Inside%E2%80%93outside%E2%80%93beginning_(tagging)) format.
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  ## Intended use
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  ## Usage
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- If you use the model in your work please use the following referrals; (model) https://doi.org/10.5281/zenodo.6980076 and (paper) https://doi.org/10.1186/s12859-022-05130-x0
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  ## References
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  Paper: Verkijk, S. & Vossen, P. (2022) MedRoBERTa.nl: A Language Model for Dutch Electronic Health Records. Computational Linguistics in the Netherlands Journal, 11.
 
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  ```
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+ The medical entity classifiers are (being) integrated in the opensource library [clinlp](https://github.com/umcu/clinlp), feel free to contact
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+ us for access, either through Huggingface or through git.
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  It is perhaps good to note that we assume the [Inside-Outside-Beginning](https://en.wikipedia.org/wiki/Inside%E2%80%93outside%E2%80%93beginning_(tagging)) format.
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  ## Intended use
 
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  ## Usage
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+ If you use the model in your work please use the following referrals; (model) https://doi.org/10.5281/zenodo.6980076 and (paper) https://doi.org/10.1186/s12859-022-05130-x
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  ## References
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  Paper: Verkijk, S. & Vossen, P. (2022) MedRoBERTa.nl: A Language Model for Dutch Electronic Health Records. Computational Linguistics in the Netherlands Journal, 11.