  Lung cancer is the leading cause of death among different types of cancers.
Every year, the lives lost due to lung cancer exceed those lost to pancreatic,
breast, and prostate cancer combined. The survival rate for lung cancer
patients is very low compared to other cancer patients due to late diagnostics.
Thus, early lung cancer diagnostics is crucial for patients to receive early
treatments, increasing the survival rate or even becoming cancer-free. This
paper proposed a deep-learning model for early lung cancer prediction and
diagnosis from Computed Tomography (CT) scans. The proposed mode achieves high
accuracy. In addition, it can be a beneficial tool to support radiologists'
decisions in predicting and detecting lung cancer and its stage.

Image and Video Processing;Computer Vision and Pattern Recognition;Machine Learning;Quantitative Methods