Abstract
Lung cancer is among the most fatal disease in developed countries, and early diagnosis of the disease is difficult. Lung cancer diagnosis and treatment has been one of the most daunting challenges humans have encountered in recent decades. Early tumor diagnosis will continue to save a vast amount of lives around the world on a daily basis. This paper describes a method for classifying lung tumors as malignant or benign that combines a Convolutional Neural Network (CNN) with the AlexNet Network Model. AlexNet CNN is one of the transfer learning models. As compared to accuracy achieved by conventional neural network systems, the proposed CNN achieves a high degree of accuracy, which is more effective.
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