Deep Learning Enabled Computer Aided Diagnosis Model for Lung Cancer using Biomedical CT Images

Early detection of lung cancer can help for improving the survival rate patients. Biomedical imaging tools such as computed tomography (CT) image was utilized to proper identification and positioning cancer. The recently developed deep learning (DL) models be employed effectual classification diseases. This article introduces novel enabled CAD technique using biomedical CT image, named DLCADLC-BCT technique. proposed intends detecting classifying images. initially uses gray level co-occurrence matrix (GLCM) model feature extraction. Also, long short term memory (LSTM) applied existence in Moreover, moth swarm optimization (MSO) algorithm is optimally choose hyperparameters LSTM rate, batch size, epoch count. For demonstrating improved classifier results approach, a set simulations were executed on benchmark dataset outcomes exhibited supremacy over recent approaches.