Evaluation patterns and algorithm for cancer identifications using dynamic clustering

Abstract

Engineering, mathematics, and even medical diagnostics all use deep data extraction for knowledge discovery and extraction. Many benchmark datasets exist in which a large amount of research is taking place in relation to genomics and medical data analytics. Data analytics and dynamic clustering are utilized to identify cancer in this research publication, which outlines the evaluation patterns and methodologies employed for this purpose. Working with medical datasets and their important properties, a data mining procedure may be trained, and thus a predictions variety can be made on various parameters.