Detection of Lung Cancer using VGG-16

Lung cancer is currently one of the most dangerous diseases that the world has faced, and it has claimed many lives. Many failed to cure this cancer because of late-stage detection. So, thereby, early detection of lung cancer is the best way to save many lives and is the best way to cure the disease, and it has become one of the deadliest diseases across the country. To prevent this, there are various techniques, here VGG-16 and CNN are selected for the detection of lung cancer because they give the best accuracy among the ones that are available. The VGG-16 is one of the famous models. By using CNN initially, it takes an image as input and then performs data pre-processing. The data will be trained, then the basic VGG-16 models will be added. First, a flatten layer will be included, followed by a normalization layer, dense layer, and finally a drop-out layer. This process will be repeated for the required number of times. Then, the model needs to be compiled, and then the model needs to fit into the training data by initializing the number of iterations. After it was fitted into the training data, the model has to be validated, and finally, the accuracy has to be tested.