Co- Disease Prediction using Multileyer Perceptron and Classification from Diabetic Medical Data Sets

  • Authors

    • Shahebaz Ahmed Khan
    • Dr. Seemakurthi
    • Dr. Akhil Jabbar
    2018-09-25
    https://doi.org/10.14419/ijet.v7i4.6.20450
  • ANN, classification methods, final classifier, co-disease and multilevel perceptron

  • Abstract

    Artificial Neural Networks (ANN) techniques have the important concepts those can be used in the present scenario of the medical world. It has made the medical field to formulate easy steps to detect and predict the diseases like diabetes, thrombocytopenia, heart diseases, brain tumor, cancer etc. The classification methods available in the data mining theories and ANN gradually help to predict the data for the future analysis by building the classification models. In this paper, the results and the research work carried out on diabetic medical data using the artificial neural network algorithms like multilevel perception and its application over such data so as to predict the      diseases are discussed. The rules developed will be helpful to detect the co-disease in the diabetic patients and we have ranked them as per the final classifier for prediction. The proposed classification algorithm has accurately predicted the data with and without feature subset selection.

     

     

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  • How to Cite

    Ahmed Khan, S., Seemakurthi, D., & Akhil Jabbar, D. (2018). Co- Disease Prediction using Multileyer Perceptron and Classification from Diabetic Medical Data Sets. International Journal of Engineering & Technology, 7(4.6), 138-140. https://doi.org/10.14419/ijet.v7i4.6.20450

    Received date: 2018-09-29

    Accepted date: 2018-09-29

    Published date: 2018-09-25