@inproceedings{06c4a3702d07477896e4d7803d7cb547,
title = "Modeling Dutch Medical Texts for Detecting Functional Categories and Levels of COVID-19 Patients",
abstract = "Electronic Health Records contain a lot of information in natural language that is not expressed in the structured clinical data. Especially in the case of new diseases such as COVID-19, this information is crucial to get a better understanding of patient recovery patterns and factors that may play a role in it. However, the language in these records is very different from standard language and generic natural language processing tools cannot easily be applied out-of-the-box. In this paper, we present a fine-tuned Dutch language model specifically developed for the language in these health records that can determine the functional level of patients according to a standard coding framework from the World Health Organization. We provide evidence that our classification performs at a sufficient level (F1-score above 80% for the main categories and error rates of less than 1 level on a 5-point Likert scale for levels) to generate patient recovery patterns that can be used to analyse factors that contribute to the rehabilitation of COVID-19 patients and to predict individual patient recovery of functioning.",
keywords = "COVID-19, Dutch language models, electronic health records, functional level classification, medical text mining",
author = "J. Kim and S. Verkijk and P. Vossen and E. Geleijn and {van der Leeden}, M. and C. Meskers and C. Meskers and {van der Veen}, S. and G. Widdershoven",
note = "{\textcopyright} European Language Resources Association (ELRA), licensed under CC-BY-NC-4.0; 13th International Conference on Language Resources and Evaluation Conference, LREC 2022 ; Conference date: 20-06-2022 Through 25-06-2022",
year = "2022",
language = "English",
series = "2022 Language Resources and Evaluation Conference, LREC 2022",
publisher = "European Language Resources Association (ELRA)",
pages = "4577--4585",
editor = "Nicoletta Calzolari and Frederic Bechet and Philippe Blache and Khalid Choukri and Christopher Cieri and Thierry Declerck and Sara Goggi and Hitoshi Isahara and Bente Maegaard and Joseph Mariani and Helene Mazo and Jan Odijk and Stelios Piperidis",
booktitle = "2022 Language Resources and Evaluation Conference (LREC 2022)",
}