메뉴 건너뛰기




Volumn 19, Issue 5, 2012, Pages 897-905

A classification approach to coreference in discharge summaries: 2011 i2b2 challenge

Author keywords

[No Author keywords available]

Indexed keywords

ANATOMY; ARTICLE; ASSERTIVENESS; CLINICAL CLASSIFICATION; HOSPITAL DISCHARGE; HOSPITAL INFORMATION SYSTEM; HOSPITAL PERSONNEL; KNOWLEDGE; MEDICAL DEVICE; PATIENT; RELATIVE; SPATIAL ANALYSIS; SUPPORT VECTOR MACHINE; SURGERY; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; CLASSIFICATION; COMPUTER SIMULATION; DATA MINING; ELECTRONIC MEDICAL RECORD; EVALUATION; HUMAN; METHODOLOGY; NATURAL LANGUAGE PROCESSING; SEMANTICS; UNITED STATES;

EID: 84872225986     PISSN: 10675027     EISSN: 1527974X     Source Type: Journal    
DOI: 10.1136/amiajnl-2011-000734     Document Type: Article
Times cited : (14)

References (31)
  • 1
    • 84872234230 scopus 로고    scopus 로고
    • Evaluating the state of the art in coreference resolution for electronic medical records
    • Uzuner Ö, Bodnari A, Shen S, et al. Evaluating the state of the art in coreference resolution for electronic medical records. J Am Med Inform Assoc 2012;19:786e91.
    • (2012) J Am Med Inform Assoc , vol.19 , pp. 786-791
    • Uzuner, Ö.1    Bodnari, A.2    Shen, S.3
  • 2
    • 84873845500 scopus 로고    scopus 로고
    • The 2011 i2b2 Challenge
    • The 2011 i2b2 Challenge. https://www.i2b2.org/NLP/Coreference/Call.php
  • 8
    • 0039891959 scopus 로고    scopus 로고
    • A machine learning approach to coreference resolution of noun phrases
    • Soon WM, Ng HT, Lim DCY. A machine learning approach to coreference resolution of noun phrases. Comput Ling 2001;27:512e44.
    • (2001) Comput Ling , vol.27 , pp. 512-544
    • Soon, W.M.1    Ng, H.T.2    Lim, D.C.Y.3
  • 14
    • 84873846054 scopus 로고    scopus 로고
    • Wikipedia
    • Wikipedia. http://www.wikipedia.org/
  • 15
    • 84873838819 scopus 로고    scopus 로고
    • Freebase
    • Freebase. http://www.freebase.com/
  • 16
    • 84873877274 scopus 로고    scopus 로고
    • WordNet
    • WordNet. http://wordnet.princeton.edu/
  • 17
    • 84873840800 scopus 로고    scopus 로고
    • Yago
    • Yago. http://www.mpi-inf.mpg.de/yago-naga/yago/
  • 19
    • 84873807514 scopus 로고    scopus 로고
    • UMLS Knowledge Base
    • UMLS Knowledge Base. http://www.nlm.nih.gov/research/umls
  • 24
    • 84873878342 scopus 로고    scopus 로고
    • SNOMED Knowledge Base
    • SNOMED Knowledge Base. http://www.nlm.nih.gov/research/umls/Snomed/ snomed_main.html
  • 25
    • 84873827561 scopus 로고    scopus 로고
    • MESH Knowledge Base
    • MESH Knowledge Base. http://www.ncbi.nlm.nih.gov/mesh
  • 26
    • 84873858342 scopus 로고    scopus 로고
    • RadLex Knowledge Base
    • RadLex Knowledge Base. http://www.radlex.org/
  • 27
    • 78149474102 scopus 로고    scopus 로고
    • Community annotation experiment for ground truth generation for the i2b2 medication challenge
    • Uzuner O, Solti I, Xia F, et al. Community annotation experiment for ground truth generation for the i2b2 medication challenge. J Am Med Inform Assoc 2010;17:519e23.
    • (2010) J Am Med Inform Assoc , vol.17 , pp. 519-523
    • Uzuner, O.1    Solti, I.2    Xia, F.3
  • 28
    • 70350788833 scopus 로고    scopus 로고
    • Evaluation of a method to identify and categorize section headers in clinical documents
    • Denny JC, Spickard A 3rd, Johnson KB, et al. Evaluation of a method to identify and categorize section headers in clinical documents. J Am Med Inform Assoc 2009;16:806e15.
    • (2009) J Am Med Inform Assoc , vol.16 , pp. 806-815
    • Denny, J.C.1    Spickard III, A.2    Johnson, K.B.3
  • 29
    • 80053292637 scopus 로고    scopus 로고
    • i2b2/VA challenge on concepts, assertions, and relations in clinical text
    • 2010
    • Uzuner O, South BR, Shen S, et al. 2010 i2b2/VA challenge on concepts, assertions, and relations in clinical text. J Am Med Inform Assoc 2011;18:552e6.
    • (2011) J Am Med Inform Assoc , vol.18 , pp. 552-556
    • Uzuner, O.1    South, B.R.2    Shen, S.3
  • 30
    • 84873831178 scopus 로고    scopus 로고
    • Multi-class SVM
    • Multi-class SVM. http://svmlight.joachims.org/svm_multiclass.html


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.