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The most deadly and life-threatening disease in the world is lung cancer.Though early diagnosis and accurate treatment are necessary for lowering thelung cancer mortality rate. A computerized tomography (CT) scan-based image isone of the most effective imaging techniques for lung cancer detection usingdeep learning models. In this article, we proposed a deep learning model-basedConvolutional Neural Network (CNN) framework for the early detection of lungcancer using CT scan images. We also have analyzed other models for instanceInception V3, Xception, and ResNet-50 models to compare with our proposedmodel. We compared our models with each other considering the metrics ofaccuracy, Area Under Curve (AUC), recall, and loss. After evaluating themodel's performance, we observed that CNN outperformed other models and hasbeen shown to be promising compared to traditional methods. It achieved anaccuracy of 92%, AUC of 98.21%, recall of 91.72%, and loss of 0.328.

LCDctCNN: Lung Cancer Diagnosis of CT scan Images Using CNN Based Model