• DocumentCode
    2078277
  • Title

    Diabetes diagnosis decision support system based on symptoms, signs and risk factor using special computational algorithm by rule base

  • Author

    Rahaman, Saifur

  • Author_Institution
    Comput. Sci. & Eng., Univ. of Chittagong, Chittagong, Bangladesh
  • fYear
    2012
  • fDate
    22-24 Dec. 2012
  • Firstpage
    65
  • Lastpage
    71
  • Abstract
    Diabetes is one of the major type of disease. It is the very common disease in the modern world. Diabetes is a serious disease that affects almost every organ in the body like heart, eyes, kidney, skin, nerves, blood vassals, foot etc. If left the disease unchecked it will make serious complications including death. However, a proper diagnosis at an early stage can result in significant life saving. Unfortunately, all the physicians are not equally skilled, which can cause for time delay, inaccuracy of the diagnosis. In the present paper, a Decision Support System has been proposed for Diabetes diagnosis. The proposed system is designed and developed by using Netbean7.1´s GUI and MySQL server feature with the implementation of The dataset used in this study are the signs, symptoms, risk factors associated with diabetes and the results of physical evaluation of a patient. This system provides a user interactive, menu driven environment. It will ask a bunch of questions about the signs, symptoms and risk factors to the system user and user should give yes or no answer. According to the answer the system will make Decision about the possibility of illness, how much severe it is like slight chance, moderate chance, high chance, very high chance, diabetic or not.
  • Keywords
    SQL; decision support systems; diseases; graphical user interfaces; interactive systems; knowledge based systems; medical computing; patient diagnosis; MySQL server feature; Netbean7.1 GUI; diabetes diagnosis decision support system; disease; high chance; illness possibility; menu driven environment; moderate chance; risk factor; rule base; sign; slight chance; special computational algorithm; symptoms; user interactive environment; very high chance; Decision Support System; Diabetes; Signs; Special Computational Algorithm by Rule Base(SCARB); risk factor and symptoms;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer and Information Technology (ICCIT), 2012 15th International Conference on
  • Conference_Location
    Chittagong
  • Print_ISBN
    978-1-4673-4833-1
  • Type

    conf

  • DOI
    10.1109/ICCITechn.2012.6509796
  • Filename
    6509796