Abstract
Temporal expressions are present in several types of texts, including clinical ones. The current research over temporal expressions has been done by the use of rule-based systems, machine learning or hybrid approaches, in most cases, over annotated (labeled) news texts correctly written in English. In this paper, we propose a method to extract and normalize temporal expressions from noisy and unlabeled clinical texts (discharge summaries) written in Brazilian Portuguese using a rule-based approach. The obtained results are similar to the state-of-the-art researches made with the same purpose in other languages. The proposed method reached a F1 score of 88.92% for the extraction step and, a F1 score of 87.89% for the normalization step.
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de Azevedo, R.F., Rodrigues, J.P.S., da Silva Reis, M.R., Moro, C.M.C., Paraiso, E.C. (2018). Temporal Tagging of Noisy Clinical Texts in Brazilian Portuguese. In: Villavicencio, A., et al. Computational Processing of the Portuguese Language. PROPOR 2018. Lecture Notes in Computer Science(), vol 11122. Springer, Cham. https://doi.org/10.1007/978-3-319-99722-3_24
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