Lung cancer prediction using machine learning techniques / Muhammad Muhaimin Mohd Fauzi and Mohd Nizam Osman

Lung, prostate, and colorectal cancers are responsible for up to 45 percent of all cancer-related deaths. Therefore, it is of the biggest significance to recognise or predict it prior to its crucial stages. It is possible to save lives by identifying and treating cancer in its earliest stages. The classification of cancer risks, such as high risk and low risk, is often achieved using statistical methods. When this occurs, it may be very difficult to handle the complex interactions of high-dimensional data. To bypass these limitations, which are caused by the vast size of the data, techniques from the area of machine learning may be used. Therefore, for the aim of this research, machine learning techniques such as K-nearest neighbours, decision tree, and logistic regression were employed to predict the probability of developing cancer.