Review on Deep Learning Technique for Detecting Non-Small Cell Lung Cancer

Abstract

The lung cancer is one of the major cancers in the world. Almost 80% of cancer we found in the world is related to lung only. We can find two different lung cancers; there are small cell lung cancer and non-small cell lung cancer. Here, we are only concentrated about the non-small cell lung cancer or (NSCLC). Here, we considered the KRAS mutation of the human gene. The KRAS biomarker is one of the main reasons for the NSCLC. Nearly 25% of the mutations happen in the form of KRAS mutation. Here, we have reviewed different deep learning and machine learning methods like convolutional neural network CNN, Support Vector Machine (SVM) and K Nearest Neighbors (KNN), to find the NSCLC. We can find different methods to compare the accuracy and precision of datasets. In this work, we tried to enhance the analysis gene for non-small cell lung cancer and detect the non-small cell lung using human genome sequence.