Classification of Non-Small Cell Lung Cancer with the Histopathology Images based on Random Forest, Decision Tree and XGBoost Algorithm

Among all types of cancer, Lung cancer has more mortality rate. Hence early detection of it may help in in increasing the life span of the patient. Histopathological images with computerised technologies can predict results accurately than human. The early detection of NSCLC lung cancer can be made possible by using histopathology images with computer aided algorithm. In this paper machine learning techniques such as XGBoost, Random Forest, and Decision Tree algorithms are discussed. This research work has used three classes of 5000 histopathological images of lung tumor tissue. It has discussed the advantages and disadvantages of using various algorithms and their prediction accuracy.