Gastric Cancer Prediction: A Comparative Analysis of Methodologies and Performances in Deep Learning Perspective
AbstractCancer is the second leading cause of death globally, and Globally, about 1 in 6 deaths is due to cancer. Among the various types of cancers gastric cancer which starts from epithelial cells on the gastric mucosa is one of the common malignancies cancer disease. In recent years,deep learning is widely used by medical professionals and researchers to discover the hidden patterns in complex images and data and thus serves the healthcare industry better. Deep learning in healthcare provides doctors the analysis of any disease accurately and helps them treat them better, thus resulting in better medical decisions.The goal of deep learning is to understand the structure of data, so that accurate predictions can be made based on the properties of that data. Huge complex datasets which are beyond the scope of human capability, can be processed using deep learning which can then reliably convert analysis of that data into clinical insights that aid physicians in planning and providing care, ultimately leading to better outcomes with lower costs. In this study, an analysis is performed for gastric cancer prediction with deep learning perspective.