Prediction and Classification Lung Cancer using Machine Learning

In wealthy nations, lung cancer is one of the most lethal diseases, and early detection is challenging. One of the most difficult problems people have faced recently is lung cancer diagnosis and treatment. Every day, early tumor diagnosis will continue to save many lives all around the world. This research presents a strategy that integrates a Convolutional Neural Network (CNN) with the AlexNet Network Model to categorize lung cancers as benign or malignant. One of the transfer learning models is AlexNet CNN. Here, in this project, the aim will be focussed onto list, discuss, and analyse several ML algorithm to classify and detect lung cancer and its stages. The proposed CNN achieves a high degree of accuracy, which is more effective than the accuracy attained by traditional neural network systems.