Early Prediction of Pancreatic Malignancy by using Deep Learning Techniques
Abirami S, Balika J Chelliah · 2024
Computer systems are having a lot of opportunity to develop with the newest technologies and are getting more efficient because of the significant study on medical healthcare systems. These breakthroughs allow the systems to automatically diagnose health-related problems. The healthcare research is focused on predicting cancer in which can affect different portions of the body. Pancreatic cancer is one of the cancers that is predicted to be remediless and it can be difficult to treat once diagnosed and it affects the pancreas, which is a crucial organ located behind the stomach. It can be challenging to detect this cancer due to its location. In the diagnosis of pancreatic cancer, oncologists conduct various tests to identify the disease and assess the severity of the patient's condition. Medical imaging has been a focus of deep learning research and it makes the process of problem diagnosis automatic. Accurately locating the pancreas is possible with current segmentation models for pancreatic cancer, but they are still not able to segment the edge. To get over these drawbacks and develop a Pancreatic malignancy detection technique that is far more accurate, economical, and predict the early stages of cancer. The research makes use of many deep learning methods, including machine learning algorithms and convolutional neural network.