Rule-based Information Extraction from Patients' Clinical Data

Anna Kupsc 1, 2, 3 Malgorzata Marciniak 2 Agnieszka Mykowiecka 2
3 SIGNES - Linguistic signs, grammar and meaning: computational logic for natural language
Université Sciences et Technologies - Bordeaux 1, Inria Bordeaux - Sud-Ouest, École Nationale Supérieure d'Électronique, Informatique et Radiocommunications de Bordeaux (ENSEIRB), CNRS - Centre National de la Recherche Scientifique : UMR5800
Abstract : The paper describes a rule-based information extraction (IE) system developed for Polish medical texts. We present two applications designed to select data from medical documentation in Polish: mammography reports and hospital records of diabetic patients. First, we have designed a special ontology that subsequently had its concepts translated into two separate models, represented as typed feature structure (TFS) hierarchies, complying with the format required by the IE platform we adopted. Then, we used dedicated IE grammars to process documents and fill in templates provided by the models. In particular, in the grammars, we addressed such linguistic issues as: ambiguous keywords, negation, coordination or anaphoric expressions. Resolving some of these problems has been deferred to a post-processing phase where the extracted information is further grouped and structured into more complex templates. To this end, we defined special heuristic algorithms on the basis of sample data. The evaluation of the implemented procedures shows their usability for clinical data extraction tasks. For most of the evaluated templates, precision and recall well above 80% were obtained.
Type de document :
Article dans une revue
Journal of Biomedical Informatics, Elsevier, 2009, 42 (5), pp.923-936. 〈10.1016/j.jbi.2009.07.007〉
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Contributeur : Anna Kupsc <>
Soumis le : mercredi 30 septembre 2009 - 12:58:17
Dernière modification le : jeudi 11 janvier 2018 - 06:22:12




Anna Kupsc, Malgorzata Marciniak, Agnieszka Mykowiecka. Rule-based Information Extraction from Patients' Clinical Data. Journal of Biomedical Informatics, Elsevier, 2009, 42 (5), pp.923-936. 〈10.1016/j.jbi.2009.07.007〉. 〈inria-00420999〉



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