Mortality Prediction of Lung Cancer from CT Images Using Deep Learning Techniques

The leading cause for the death in humans is cancer. One of the most common cancers is lung cancer and deadly cancers, causing significant harm to the human body. Cancer must be detected early in order to be cured. Many lives can be spared if lung cancer is detected early. To achieve better results, a Computerised System deep-learning can be implemented. The main purpose of this research is to develop models employing a variety of Deeping Learning models. Classifier and to forecast the mortality prediction and to identify which the (NSCLC) Non-Small-Cell-lung-Cancer diseases are affected severe and this disease can be treated accordingly. To determine which of the two models is the best. In this research, the Resnet18, Resnet50, Resnet101 are used as architectural model to predict the lung cancer disease Several performance metrices were used to analyse these models, and the result of those performances metrices show that the Convolutional neural network classifier is the best model than support vector machine.