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

In the EXISTING SYSTEM 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) &. Based on these three clustering was formed if an dataset is not fit into these three category it will be considered as outlier and the data will not pass to the user. In the MODIFICATION part, rather than mere purchase model we implement for 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(Electrical and Electronics Engg), B.E(Electronics and Communication), B.E(Information Technology),
  • Domain
  • Cloud Computing, Data Mining,
  • Technology
  • .Net,
  • Avilable city
  • Chennai,

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AADHITYAA INFOMEDIA SOLUTIONS, T.NAGAR

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