Lung Cancer Detection Using Machine Learning

Lung cancer ranks among the primary causes of death on global scale. Catching this disease early can increase your chances or opportunities of survival. Computer-assisted detection (CAD) is used to create CT images and even X-rays of the lungs to determine whether cancer is present in the images. This paper represents an image classification by the combination of a neural network (CNN) algorithm and support vector machine (SVM). The algorithm spontaneously separates and analyzes lung picture or image to detect cancer cells. Compared to full-scale networks, CNNs are easier to train and have less overhead. We introduce CNN-SVM because it has accurate performance than other existing terminologies. The merits of this method are that it can detect cancer on the CT image