A Systematic Review Of Lung Cancer Prediction Using Machine Learning Algorithm

Detecting lung cancer is difficult and dangerous. Males and females are both at risk of dying from it, so it is especially important to examine nodules immediately and correctly. As a result, different methodologies have been established for the prevention of lung cancer. In this paper, a comparison of different methods of using machine learning and deep learning to determine lung cancer risk is discussed. Over the past few decades, several methods have been developed to diagnose lung cancer, including CT scans and X-rays. Additionally, a variety of classifiers and segmentation algorithms could be deployed in order to detect lung cancer nodules by recognizing images. CT scan images were found to provide more accurate results from this study. In fact, lung cancer is the common cancer type that causes death, CT scan is the best way to diagnose. This paper reviews the literature concerning various techniques for preprocessing, nodule segmentation, and classification.