Deep Learning for Lung Cancer Detection and Classification

Electronics and Communication Engineering

Deep learning has a lot of potential to help us detect and classify lung cancer more accurately, which is really important for early detection and treatment. Two of the most well-known deep CNN models are VGG16 and VGG19 These deep CNN models are well-known for their depth and great feature extraction abilities, but they've been adapted and finely-tuned to analyze medical images, especially chest X-rays or CT scans. This allows us to automatically recognize complex patterns and features in the lung images, so we can more accurately differentiate between the benign and malignant lung nodules or lesions. In this abstract, we'll look at the architectural details of these models, how they can be applied through transfer learning to lung cancer datasets, as well as how data augmentation techniques can be used to improve model generalization. All in all, these models can help us improve the detection and treatment of lung cancer, reduce mortality rates, and provide valuable insights to healthcare professionals.

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