Lung Cancer Prediction Using Machine Learning Algorithms on Big Data: Survey

Abstract

Lung cancer is a malignant lung tumour that is characterised by the regulated growth of cells in the lung tissue. The most common cancer diagnosed worldwide is lung cancer. More deaths than any other kind of cancer occur due to lung cancer. Early diagnosis and care are very useful and efficient for the survival of cancer patients. Different image processing and soft computing methods may be used for identifying cancer cells from medical images. Classification depends on features extracted from the images. In order to produce better classification results, the focus is on the feature extraction level. In order to distinguish a pattern that can provide some useful insights into what combination of features is most likely to result in an abnormality, this knowledge is then given to machine learning algorithms. The prediction of lung cancer is analysed using various machine learning classification algorithms such as Naive Bayes, Support Vector Machine, Artificial Neural Network and Logistic Regression. The key aim of this paper is to diagnose lung cancer early by examining the performance of exist classification algorithms.