Lung Cancer Prediction using CNN

The management and early identification of lung cancer, which is known for its difficult treatment processes and high fatality rates, are crucial for successful treatment outcomes. While traditional imaging techniques like X-rays, CT scans, and MRIs have shown limitations in early detection sensitivity, the use of Convolutional Neural Networks (CNNs) offers a notable advancement, receiving acclaim for their precision in image analysis. This research delves into the impact of CNNs on detecting lung cancer, employing a secondary qualitative analysis to collate relevant data from various sources. It aims to identify and classify malignant lung nodules and the severity of lung cancer using the Inception V3 model, emphasizing the role of advanced deep learning methods in pinpointing the exact locations of these nodules.