Cancer is one of the deadliest and most ubiquitous diseases, causing a high number of fatalities each year. Lung cancer has the greatest fatality rate of all cancer kinds and primarily affects the pulmonary nodules in the lungs. Early lung cancer detection is crucial for improving patient survival. A radiologist can benefit greatly from an intelligent computer-aided diagnosis system for detecting, forecasting, and diagnosing lung cancer. Numerous researchers from around the globe have identified dozens of volatile organic molecules as biomarkers for lung cancer. The human body odour is influenced by eating habits, the environment, and a number of other factors, resulting in a great deal of diversity, and the sample sizes were inadequate, so the conclusions of different researchers were not consistent. Analysis of exhaled breath can be utilised in the early detection of lung cancer. CT scans are utilised for the diagnosis of lung cancer because they provide a detailed image of the tumour and follow its progress. Fuzzy logic, support vector machines, and statistical classifiers perform pattern matching and confirmation to improve the accuracy of the identification phase. In the following, we describe the methods and procedures utilised to identify lung cancer.