• DocumentCode
    579944
  • Title

    Automatic Diagnosis of Asthma Using Neurofuzzy System

  • Author

    Ansari, A.Q. ; Gupta, Neeraj K. ; Ekata, E.

  • Author_Institution
    Dept. of Electr. Eng., Jamia Millia Islamia, New Delhi, India
  • fYear
    2012
  • fDate
    3-5 Nov. 2012
  • Firstpage
    819
  • Lastpage
    823
  • Abstract
    In this paper, automatic diagnosis of asthma usingneurofuzzy approaches are presented. Adaptive Neural Fuzzy Inference System(ANFIS) is put in the framework of adaptive systems to facilitate learning and adaptation which uses back propagation algorithm to reduce the error in the output. In first phase input variables are prepared by taking a healthy person as a reference and in second phase these inputs with asthma patient are given to ANFIS to obtain output. Simulated result shows the proposed work for automated diagnosis, which have performed by using the realistic causes of asthma disease are effective.
  • Keywords
    backpropagation; diseases; fuzzy reasoning; medical computing; neural nets; patient diagnosis; ANFIS; adaptive neural fuzzy inference system; asthma disease; asthma patient; automatic asthma diagnosis; back propagation algorithm; learning; neurofuzzy system; Adaptive systems; Computer architecture; Input variables; Medical diagnostic imaging; Medical services; Neural networks; Training; Asthma; Backpropagation; Neurofuzzy system;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Intelligence and Communication Networks (CICN), 2012 Fourth International Conference on
  • Conference_Location
    Mathura
  • Print_ISBN
    978-1-4673-2981-1
  • Type

    conf

  • DOI
    10.1109/CICN.2012.55
  • Filename
    6375228