• DocumentCode
    2950556
  • Title

    Sequential pattern mining to discover relations between genes and rare diseases

  • Author

    Béchet, Nicolas ; Cellier, Peggy ; Charnois, Thierry ; Cremilleux, Bruno ; Jaulent, Marie-Christine

  • Author_Institution
    GREYC, Univ. de Caen Basse-Normandie, Caen, France
  • fYear
    2012
  • fDate
    20-22 June 2012
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    Orphanet provides an international web-based knowledge portal for rare diseases including a collection of review articles. However, reviews and literature monitoring are manual. Thus, new documentation about a rare disease is a time-consuming process and automatically discovering knowledge from a large collection of texts is a crucial issue. This context represents a strong motivation to address the problem of extracting gene-rare diseases relationships from texts. In this paper, we tackle this issue with a cross-fertilization of information extraction and data mining techniques (sequential pattern mining under constraints). Experiments show the interest of the method for the documentation of rare diseases.
  • Keywords
    Internet; data mining; diseases; health care; information retrieval; medical computing; portals; text analysis; Orphanet; automatic knowledge discovery; data mining technique; gene-rare diseases relationship extraction problem; information extraction technique; international Web-based knowledge portal; rare diseases; relation discovery; sequential pattern mining; Data mining; Diseases; Itemsets; Natural language processing; Pragmatics; Training;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer-Based Medical Systems (CBMS), 2012 25th International Symposium on
  • Conference_Location
    Rome
  • ISSN
    1063-7125
  • Print_ISBN
    978-1-4673-2049-8
  • Type

    conf

  • DOI
    10.1109/CBMS.2012.6266367
  • Filename
    6266367