• DocumentCode
    3425881
  • Title

    Mining electronic medical records for patient care patterns

  • Author

    Buczak, Anna L. ; Moniz, Linda J. ; Feighner, Brian H. ; Lombardo, Joseph S.

  • Author_Institution
    Johns Hopkins Univ. Appl. Phyiscs Lab., Laurel, MD
  • fYear
    2009
  • fDate
    March 30 2009-April 2 2009
  • Firstpage
    146
  • Lastpage
    153
  • Abstract
    A novel approach for generating full Electronic Medical Records of synthetic victims is described. Special emphasis is put on the data mining steps that build patient care models and perform clustering of this highly dimensional data set. A methodology for cluster validation is proposed. Results for a large data set with Staphylococcus aureus and Methicillin-Resistant Staphylococcus aureus infections are presented.
  • Keywords
    data mining; diseases; medical computing; medical information systems; patient care; pattern clustering; data mining; dimensional data set clustering; disease surveillance system; electronic medical record mining; patient care pattern model; synthetic victim; Control systems; Data mining; Diseases; Electronic equipment testing; Medical control systems; Medical tests; Sensitivity and specificity; Social network services; Surveillance; System testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Intelligence and Data Mining, 2009. CIDM '09. IEEE Symposium on
  • Conference_Location
    Nashville, TN
  • Print_ISBN
    978-1-4244-2765-9
  • Type

    conf

  • DOI
    10.1109/CIDM.2009.4938642
  • Filename
    4938642