Evaluation patterns and algorithm for cancer identifications using dynamic clustering

Abstract

The domain of knowledge discovery and deep data extraction is quite prominent and used in assorted domains including engineering, mathematics and even in medical diagnosis. A number of benchmark datasets are available in which huge research work is going on with the enormous aspects of genomics that is associated with the medical data analytics. In this research manuscript, the work presents the evaluation patterns and the approaches which are used for the cancer identification with the use of dynamic clustering and deep data analytics. The work is having the elements with the medical datasets and their key features by which the training of data in the data mining algorithm can be integrated and then the overall predictions can be done on assorted parameters.