메뉴 건너뛰기




Volumn 10988 LNCS, Issue , 2018, Pages 264-279

Improving clinical named entity recognition with global neural attention

Author keywords

Clinical named entity recognition; Language model; Neural attention

Indexed keywords

COMPUTATIONAL LINGUISTICS; INFORMATION MANAGEMENT; MEDICAL COMPUTING; NETWORK ARCHITECTURE;

EID: 85051110734     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-319-96893-3_20     Document Type: Conference Paper
Times cited : (33)

References (27)
  • 4
    • 85016097618 scopus 로고    scopus 로고
    • Named entity recognition with bidirectional LSTM-CNNs
    • Chiu, J.P.C., Nichols, E.: Named entity recognition with bidirectional LSTM-CNNs. In: Proceedings of TACL, pp. 357–370 (2016)
    • (2016) Proceedings of TACL , pp. 357-370
    • Chiu, J.P.C.1    Nichols, E.2
  • 6
    • 80053241946 scopus 로고    scopus 로고
    • Machine-learned solutions for three stages of clinical information extraction: The state of the art at i2b2 2010
    • de Bruijn, B., Kiritchenko, C.C., Martin, J.D., Zhu, X.D.: Machine-learned solutions for three stages of clinical information extraction: the state of the art at i2b2 2010. J. Am. Med. Inf. Assoc. 18(5), 557–562 (2011)
    • (2011) J. Am. Med. Inf. Assoc. , vol.18 , Issue.5 , pp. 557-562
    • de Bruijn, B.1    Kiritchenko, C.C.2    Martin, J.D.3    Zhu, X.D.4
  • 11
    • 84856376731 scopus 로고    scopus 로고
    • Enhancing clinical concept extraction with distributional semantics
    • Jonnalagadda, S., Cohen, T., Wu, S.T., Gonzalez, G.: Enhancing clinical concept extraction with distributional semantics. J. Biomed. Inf. 45(1), 129–140 (2012)
    • (2012) J. Biomed. Inf. , vol.45 , Issue.1 , pp. 129-140
    • Jonnalagadda, S.1    Cohen, T.2    Wu, S.T.3    Gonzalez, G.4
  • 18
    • 85051107916 scopus 로고    scopus 로고
    • An attention-based BiLSTM-CRF approach to document-level chemical named entity recognition
    • Luo, L., Yang, Z.H., Yang, P., Zhang, Y., Wang, L., Lin, H.F., Wang, J.: An attention-based BiLSTM-CRF approach to document-level chemical named entity recognition. Bioinformatics 1, 8 (2017)
    • (2017) Bioinformatics , vol.1 , Issue.8
    • Luo, L.1    Yang, Z.H.2    Yang, P.3    Zhang, Y.4    Wang, L.5    Lin, H.F.6    Wang, J.7
  • 25
    • 80053292637 scopus 로고    scopus 로고
    • 2010 i2b2/VA challenge on concepts, assertions, and relations in clinical text
    • Uzuner, O., South, B.R., Shen, S.Y., DuVall, S.L.: 2010 i2b2/VA challenge on concepts, assertions, and relations in clinical text. J. Am. Med. Inf. Assoc. 18(5), 552–556 (2011)
    • (2011) J. Am. Med. Inf. Assoc. , vol.18 , Issue.5 , pp. 552-556
    • Uzuner, O.1    South, B.R.2    Shen, S.Y.3    Duvall, S.L.4


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.