Rank Based Data Ming (RBDM) of Bio-Medical Large Unstructured Datasets
Medical datasets method differ in the degree to which they attempt to deal with different complicating aspects of diagnosis such as relative importance of symptoms, varied indication Data and the relation between diseases themselves. Though data mining has major benefits over the other methods, but it has many rules make many difficulties while taking Decisions. Therefore, it is essential to minimize the decision rules by using Rank based data mining; we can easily classify the patients’ medical status and also making decisions of further treatment. This work will helpful for making decisions in medical analysis. It uses Rank based Data mining for making the expected outcome. To arrange the existing problem that will overcome with a novel Rank based Data mining (RBDM) algorithm is used to tool for effective and real access to data. We proposed Rank based data mining algorithm is estimated at good scalability and performance across the widely varying computational features of data mining. The main theme of this plan is to store medical information of patients who come for hospitalization for diagnosis and algorithms are run on that information.
Author Name: K.L. Soni and M. Thirunavukkarasu
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Keywords: Data Mining, Rank Based Data Mining (RBDM), Bio-Medical Large Unstructured Datasets.