A CNN Based Machine Learning Scheme to Detect Lung Cancer Detection from CT Scan Images

The major cause of mortality in today’s globe is lung cancer. As a result, respiratory organ nodules, which are round or oval-shaped growths of scar tissues, must be identified properly and quickly in order to prevent lung cancer from developing. As a result of critical tasks, oxygen to the human body is provided by lungs while carbon dioxide is excreted; require early identification of malignant cells. In order to reduce the chance of mortality, it is critical to begin therapy by detecting cancer using a CT scan. The suggested technique involves changing the parameters, combinations that are dynamically pooled, dropout procedures that are added, and linear unit functions that are corrected (ReLu) to build a model for detecting lung cancer and categorizing tumors discovered in the lungs as malignant or benign. To forecast greater accuracy, this projected method is compared to the pre-trained model VGG16. This scheme will make it easier for doctors to give early treatment and reduce mortality.