A Web Application for Lung Cancer Analysis and Detection using Deep Learning Approach

Lung cancer is one of the most common and deadly cancers worldwide. One of the most effective ways to fight canceris todiscoveritearlyenoughtoimprovethepatient’s chances ofsurvival.TheDiscovery oflung canceratanearly stage helpsin reducing its risk. Various technologies like MRI, isotopes, X-rays, and CT scans are used for diagnosis of lung cancer. The studying of lung nodules helps a doctor to determine if the patient is malignant. These nodules sometimes have a chance of growing undetectedbythenakedeye. In thisproject,Lungcancer stageis detectedwith the help of patientdetails, symptomsand CT scans by using Machine learning and Deep learning algorithms with open-source datasets. The proposed approach uses Machine learning algorithms to study past medical records and determine if the patient has lung cancer. Deep learning models are used to analyze the CT scans to determine the stage of lung cancer. Themajorgoal of thisproject isto find nodules as small as 3 mm to detect cancer stage accurately. Finally, the machine learning model calculates the patient’s estimated medical insurance costs. This project is useful for the early detection of lung cancer in individuals and can help them in overcomingthese health conditions. The effectiveness of cancer prediction systems helps the people to know their cancer risk with low cost and it also helps the people to take the appropriate decision based on their cancer risk status.