MACHINE LEARNING APPROACH IN DISEASE DIAGNOSIS WITH ANALYSIS OF DISEASE, SYMPTOMS & TESTS IN CLOUD

there is no clustering techniques were followed in message passing. In the PROPOSED MODEL based on the affinity propagation the newly arrived objects were clustered. In this each data sets were categorized into three major Varieties namely Categories Product (Name), Objects (Variety – Eg. Manufacturers), Attributes (Sub Category – Eg Model Number) & if an dataset is not fit into these three category it will be considered as outlier and the data is not processed. In the MODIFICATION part, the same implementation is achieved on Disease Diagnosis Process We use veka tool & machine learning technique in this project. We consider disease name, symptoms & biomedical analysis for automatic disease diagnosis process.

  • Project Category : IEEE Projects
  • Project Year : 2014-2015
  • Department
  • B.E(Computer Science) , B.E(Information Technology), BCA, MCA,
  • Domain
  • Cloud Computing, Data Mining,
  • Technology
  • J2EE, J2ME, Java,
  • Avilable city
  • Chennai,

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AADHITYAA INFOMEDIA SOLUTIONS, T.NAGAR

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