Kazan (Volga region) Federal University, KFU
KAZAN
FEDERAL UNIVERSITY
 
MULTIPLE FEATURES FOR CLINICAL RELATION EXTRACTION: A MACHINE LEARNING APPROACH
Form of presentationArticles in international journals and collections
Year of publication2020
Языканглийский
  • Alimova Ilseyar Salimovna, author
  • Tutubalina Elena Viktorovna, author
  • Bibliographic description in the original language Alimova I, Tutubalina E., Multiple features for clinical relation extraction: A machine learning approach//Journal of Biomedical Informatics. - 2020. - Vol.103, Is.. - Art. № 103382.
    Keywords Relation extraction, Electronic health records, Natural language processing, Machine learning, Clinical data, Features, MADE corpus, n2c2 corpus
    The name of the journal Journal of Biomedical Informatics
    URL https://www.scopus.com/inward/record.uri?eid=2-s2.0-85079558624&doi=10.1016%2fj.jbi.2020.103382&partnerID=40&md5=f4c92a675a4d6fa6bd4074024ea0467c
    Please use this ID to quote from or refer to the card https://repository.kpfu.ru/eng/?p_id=248250&p_lang=2

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