Lung Cancer Detection using Machine Learning
S Bharathy, R Pavithra, B Akshaya.
Abstract
Lung disease is one of the most common disease that is affected in our early stage to improve the rate of patients survival.For the radiologist the diagnosis of cancer is the most challenging part.An intelligent computer aided system is very much helpful for radiologist. Various studies for detection of lung cancer with the ML techniques. To predict the lung cancer mostly multi-stage classification is used.The classification system used for data enhancement and segmentation has been done. The segmentation method uses Threshold and marker-controlled watershed and binary classifier for classification method Lung cancer detection has higher degree of accuracy. The dataset is trained with various algorithms like Support Vector Machine (SVM), K- Nearest Neighbour, Decision Tree, Logistic Regression, Naïve Bayes and Random Forest using these algorithms higher accuracy is proven. An enhanced performance level of 88.5% accuracy has been produced with the Random forest algorithm.