Lung cancer detection using convolutional neural network and transfer learning

Lung cancer has emerged as a significant cause for concern among individuals worldwide. Consequently, several nations provide financial resources and extend invitations to researchers and medical professionals to collaborate in addressing this issue. Lung cancer is a significant contributor to mortality subsequent to heart illness. The timely identification of lung cancer in its first stages has the potential to enhance patient survival rates. The use of Computer Vision is of utmost importance in the timely identification of lung cancer and the implementation of early therapeutic interventions, hence enhancing the likelihood of patient survival. The proposed deep learning model incorporates Convolutional Neural Network (CNN) and transfer learning techniques, along with other image processing methods like image compression and picture enhancement. These approaches are used to analyze medical images and make correct predictions. Our study demonstrates a CNN model accuracy of 91.29% and a transfer learning accuracy of 95.9%.