Pancreatic Cancer Detection using Machine and Deep Learning Techniques
Anish Gupta, Apeksha Koul, Yogesh Kumar
Abstract
Despite substantial research, pancreatic cancer has a terrible prognosis by having a survival rate of five years only. The premise behind early detection and better survival is that more people will benefit from a possible treatment. In general health care, machine and deep learning algorithms have shown to be a viable tool to classify or detect the risk of pancreatic cancer. As a result, in this work, we looked into various researchers' methods for diagnosing pancreatic cancer using machine and deep learning models. In addition, the report highlighted their achievements and the obstacles that remain in this sector. We incorporated our evaluation of the numerous strategies available to make some conclusions.