Abstract
This paper presents the results of testing two approaches in the automatic semantic labeling of medical data. For a chosen domain (diabetic patients’ discharge records) a set of domain related concepts was identified. The annotated resource is the result of a rule based application, that relies on the results of two related rule based information extraction (IE) systems, post processed in a way that makes the label structures simpler, and the boundaries of annotations more precise. The second application is a machine learning (CRF) approach in which the results of the first application are used as training data. Both applications were evaluated by comparing to manually corrected documents.
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Mykowiecka, A., Marciniak, M. (2011). Automatic Semantic Labeling of Medical Texts with Feature Structures. In: Habernal, I., Matoušek, V. (eds) Text, Speech and Dialogue. TSD 2011. Lecture Notes in Computer Science(), vol 6836. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23538-2_7
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DOI: https://doi.org/10.1007/978-3-642-23538-2_7
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