Application of machine learning in lung cancer prediction

Lung cancer is a life-threatening disease that is mainly caused by long-term smoking, and genetic reasons. This disease is terribly difficult to treat, but the survival rate can be largely increased by an early diagnosis. However, most people with lung cancer are not detected until the late stage. In recent years, many researchers have developed effective pre-diagnosis methods based on machine learning techniques. Machine learning technique enables the computer to learn from data and perform tasks. This review paper lists machine learning models that can be applied to lung cancer probability prediction. The models are trained by datasets of three types of backgrounds: genetic data, clinical data, and histological data. Each model uses different machine learning algorithms, and all of the models perform excellent ability in predicting. This paper suggests that machine learning models can be applied in screening for lung cancer.