Near The Beginning of Non Small Cell Lung Cancer Avoidance in Human Way of Life Risk Factors Classification Using Clustering Algorithm in the R Environment

Abstract

Cancer dominance is on the rise. The Lung Cancer is the Uncontrolled growth of abnormal cells that start off in one or both Lung Usually in the cell that Line the air Passages. The Two main types are Small Cell Lung Cancer and Non-Small Cell Lung Cancer. NSCLC is a complex disease which is characterized by the gathering of human behavior deviation for the duration of the human’s lifetime. The prevention of NSCLC is an important and tedious task in medicine. The aim of this paper predicts the NSCLC using clustering algorithm. The attribute selection method is used to reduce the risk factors. The human routine life risk factors are classified into three levels. There are you can change, you cannot change, uncertain or unproven effects of lung cancer. The risk factors are classified using k-means clustering and hierarchical clustering; we identified the best performing of clustering methodology in the context of clinical outcome. Ultimate goal of this research work is to find out which type of clustering algorithm will be most suitable for analysis of Non Small Cell Lung Cancer data.