• DocumentCode
    3225654
  • Title

    An intelligent agent for detection of erythemato- squamous diseases using Co-active Neuro-Fuzzy Inference System and genetic algorithm

  • Author

    Parthiban, Latha ; Subramanian, R.

  • Author_Institution
    Dept. of Comput. Sci. & Eng., Aaarupadai Veedu Inst. of Technol., Chennai, India
  • fYear
    2009
  • fDate
    22-24 July 2009
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    In this paper, a new approach based on coactive neuro-fuzzy inference system (CANFIS) is presented for detection of erythemato-squamous diseases. The domain contained records of patients with 34 features and known diagnosis of six disease indications. Given a training set of such records, the CANFIS classifiers learned how to differentiate a new case in the domain that may be difficult even for experienced doctors to make correct diagnosis because many symptoms look very similar to each other, even though they are caused by different diseases. The proposed CANFIS model combined the neural network adaptive capabilities and the fuzzy logic qualitative approach which is then integrated with genetic algorithm. The performances of the CANFIS model were evaluated in terms of training performances and classification accuracies and the results showed that the proposed CANFIS model has great potential in detecting the erythemato-squamous diseases.
  • Keywords
    biology computing; diseases; fuzzy logic; fuzzy set theory; genetic algorithms; inference mechanisms; multi-agent systems; neural nets; coactive neuro-fuzzy inference system; erythemato-squamous disease detection; fuzzy logic qualitative approach; genetic algorithm; intelligent agent; neural network adaptive capabilities; Adaptive systems; Artificial neural networks; Computer science; Diseases; Fuzzy logic; Fuzzy neural networks; Fuzzy systems; Genetic algorithms; Intelligent agent; Performance evaluation; Artificial Neural Networks; Coactive Adaptive Neuro-Fuzzy Inference System (CANFIS); Erythemato-Squamous diseases; Fuzzy Logic; Genetic Algorithm (GA);
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Agent & Multi-Agent Systems, 2009. IAMA 2009. International Conference on
  • Conference_Location
    Chennai
  • Print_ISBN
    978-1-4244-4710-7
  • Type

    conf

  • DOI
    10.1109/IAMA.2009.5228016
  • Filename
    5228016