Lung Cancer Classification Using Deep Learning Hybrid Model

Abstract

Abnormal growths in the lungs caused by disease. The classification of CT scans is accomplished by applying machine learning strategies. Classification methods based on deep learning, such as support vector machines, can categorize a wide variety of image datasets and produce segmentation results of the highest caliber. In this work, we suggested a method for deep feature extraction from images by altering SVM and CNN and then applying the hybrid model resulting from those modifications (NNSVLC). For this investigation, the Kaggle dataset will be utilized. The proposed method was found to be accurate 91.7% of the time, as determined by the results of the experiments.