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

 
 
 
  • Abstract
  • Keywords
  • References
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  • 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.

     

     


  • Keywords


    ANN, classification methods, final classifier ,co-disease and multilevel perceptron

  • References


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Article ID: 20450
 
DOI: 10.14419/ijet.v7i4.6.20450




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