• DocumentCode
    595612
  • Title

    A novel data-mining approach leveraging social media to monitor and respond to outcomes of diabetes drugs and treatment

  • Author

    Akay, Altug ; Dragomir, Andrei ; Erlandsson, Bjorn-Erik

  • Author_Institution
    Sch. of Technol. & Health, R. Inst. of Technol., Huddinge, Sweden
  • fYear
    2013
  • fDate
    16-18 Jan. 2013
  • Firstpage
    264
  • Lastpage
    266
  • Abstract
    A novel data-mining method was developed to gauge the experiences of medical devices and drugs by patients with diabetes mellitus. Self-organizing maps were used to analyze forum posts numerically to better understand user opinion of medical devices and drugs. The end-result is a word list compilation that correlates certain positive and negative word cluster groups with medical drugs and devices. The implication of this novel data-mining method could open new avenues of research into rapid data collection, feedback, and analysis that would enable improved outcomes and solutions for public health.
  • Keywords
    biomedical equipment; data mining; diseases; drugs; medical computing; patient monitoring; patient treatment; social networking (online); data collection; diabetes drug; diabetes mellitus; diabetes treatment; medical device; negative word cluster group; novel data-mining approach leveraging social media; positive word cluster group; public health; self-organizing map; Data mining; Diabetes; Drugs; Educational institutions; Media; Vectors;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Point-of-Care Healthcare Technologies (PHT), 2013 IEEE
  • Conference_Location
    Bangalore
  • Print_ISBN
    978-1-4673-2765-7
  • Electronic_ISBN
    978-1-4673-2766-4
  • Type

    conf

  • DOI
    10.1109/PHT.2013.6461335
  • Filename
    6461335