• DocumentCode
    2337112
  • Title

    Association analysis of diabetes mellitus (DM) with complication states based on association rules

  • Author

    Kasemthaweesab, P. ; Kurutach, W.

  • Author_Institution
    Fac. of Inf. Sci. & Technol., Mahanakorn Univ. of Technol., Bangkok, Thailand
  • fYear
    2012
  • fDate
    18-20 July 2012
  • Firstpage
    1453
  • Lastpage
    1457
  • Abstract
    Currently data mining techniques and health/medical informatics are still new. Data mining researchers start paying more attention on these matters. Association Rule is one of important methods in data mining. By discovering data association, new useful information can be obtained. In this paper, a researcher has presented a basic method of discovering an association of diabetes mellitus with complication states by applying gender, age and occupation factors and testing to find out a relationship of diagnostic data. The primary objective is to provide a useful medical and healthcare information that can be applied for a treatment of elderly-adult patients, an improvement of healthcare service including a provision of practical instruction for diabetes patients without complications.
  • Keywords
    data mining; geriatrics; health care; medical information systems; patient treatment; sensor fusion; DM; association analysis; association rules; data association; data mining; diabetes mellitus; elderly-adult patient treatment; health/medical informatics; healthcare information; Aging; Association rules; Databases; Diabetes; Diseases; Medical diagnostic imaging; Association Rule; Data mining; Diabetes Mellitus;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Industrial Electronics and Applications (ICIEA), 2012 7th IEEE Conference on
  • Conference_Location
    Singapore
  • Print_ISBN
    978-1-4577-2118-2
  • Type

    conf

  • DOI
    10.1109/ICIEA.2012.6360952
  • Filename
    6360952