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Volumn 32, Issue 19, 2016, Pages 3044-3046

Meshable: Searching PubMed abstracts by utilizing MeSH and MeSH-derived topical terms

Author keywords

[No Author keywords available]

Indexed keywords

DOCUMENTATION; MEDICAL SUBJECT HEADINGS; MEDLINE; SEARCH ENGINE;

EID: 84990912971     PISSN: 13674803     EISSN: 14602059     Source Type: Journal    
DOI: 10.1093/bioinformatics/btw331     Document Type: Article
Times cited : (30)

References (12)
  • 2
    • 84942914672 scopus 로고    scopus 로고
    • Thematic clustering of text documents using an EM-based approach
    • Kim, S. and Wilbur, W.J. (2012) Thematic clustering of text documents using an EM-based approach. J. Biomed. Semant., 3, S6.
    • (2012) J. Biomed. Semant. , vol.3 , pp. S6
    • Kim, S.1    Wilbur, W.J.2
  • 3
    • 84928737551 scopus 로고    scopus 로고
    • Identifying named entities from PubMed for enriching semantic categories
    • Kim, S. et al. (2015a) Identifying named entities from PubMed for enriching semantic categories. BMC Bioinformtics, 16, 57.
    • (2015) BMC Bioinformtics , vol.16 , pp. 57
    • Kim, S.1
  • 5
    • 0034832550 scopus 로고    scopus 로고
    • Corpus-based statistical screening for content-bearing terms
    • Kim, W. and Wilbur, W.J. (2001) Corpus-based statistical screening for content-bearing terms. J. Am. Soc. Inform. Sci. Technol., 52, 247-259.
    • (2001) J. Am. Soc. Inform. Sci. Technol. , vol.52 , pp. 247-259
    • Kim, W.1    Wilbur, W.J.2
  • 8
    • 79953790954 scopus 로고    scopus 로고
    • LigerCat: Using "meSH clouds" from journal, article, or gene citations to facilitate the identification of relevant biomedical literature
    • Sarkar, I.N. et al. (2009) LigerCat: using "MeSH clouds" from journal, article, or gene citations to facilitate the identification of relevant biomedical literature. In: AMIA Annu. Symp. Proc., 2009, pp. 563-567.
    • (2009) AMIA Annu. Symp. Proc. , vol.2009 , pp. 563-567
    • Sarkar, I.N.1
  • 10
    • 84855963056 scopus 로고    scopus 로고
    • MeSHy: Mining unanticipated PubMed information using frequencies of occurrences and concurrences of MeSH terms
    • Theodosiou, T. et al. (2011) MeSHy: Mining unanticipated PubMed information using frequencies of occurrences and concurrences of MeSH terms. J. Biomed. Inform., 44, 919-926.
    • (2011) J. Biomed. Inform. , vol.44 , pp. 919-926
    • Theodosiou, T.1
  • 12
    • 71149117321 scopus 로고    scopus 로고
    • MedLDA: Maximum margin supervised topic models for regression and classification
    • Zhu, J. et al. (2009) MedLDA: maximum margin supervised topic models for regression and classification. In Proc. International Conference on Machine Learning (ICML), pp. 1257-1264.
    • (2009) Proc. International Conference on Machine Learning (ICML) , pp. 1257-1264
    • Zhu, J.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.