A Novel Approach to Predict Disease and Avoid Congestion in Data Mining Using Genetic Algorithm

 
 
 
  • Abstract
  • Keywords
  • References
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  • Abstract


    Presently days the health segment contains concealed information that can be critical in deciding. It is troublesome for medical professionals to anticipate the disease as it is really an intricate errand that requires experience and information. The objective of the examination is to anticipate conceivable disease from the patient dataset utilizing data mining systems and to organize the patients based on their genuine conditions to lessen the blockage in the system. In this paper we propose proficient acquainted order algorithm utilizing genetic methodology for disease expectation. The principle inspiration for utilizing genetic algorithm as a part of the disclosure of abnormal state forecast rules is that the found rules are exceptionally conceivable, having high prescient precision and of high interestingness values.

     

     

  • Keywords


    Data Mining, Association Rule, Keyword Based Clustering, Genetic algorithm, Classification.

  • References


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Article ID: 26740
 
DOI: 10.14419/ijet.v7i3.20.26740




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