Early Detection of Lung Cancer using Soft Computing - A Review

Cancer is one of the most dangerous diseases a human can ever had and lung cancer is one of them. Lung is an important organ in a human body which performs function in both respiratory system and circulatory system. Lung cancer is a disease that occurs due to the uncontrolled cell growth in tissues of the lung. In recent years, Lung cancer is one of the most growing diseases in the world due to smoking. It is very difficult to detect it in its early stages as its symptoms appear only in the advanced stages. The early detection of lung cancer is very essential to provide the timely treatment so that the probability of curing the disease increases. Lung cancer can be diagnosed using soft computing by the application of image mining techniques such as classification and clustering. Soft computing techniques such as fuzzy sets, neural networks, genetic algorithms, and rough sets are most widely applied for lung Cancer prognosis and diagnosis using medical imaging techniques. The objective of this study is to improve the lung cancer prediction with the application of soft-computing techniques.