Liver Cancer Patient Age Prediction Using Classification Comparison and Feature Selection

Abstract

Cancer is one of the deadliest diseases in the world. Cancer spreads to the liver, bones, breast, lungs, and other organs. Hepatitis B and C, liver cirrhosis, and every one of these factors contribute to the growth of liver cancer. The deadliest type of cancer is liver cancer, which is a lifetime condition. Based on WHO studies, there are about 30 cases of liver cancer per 100,000 individuals, with the majority of them originating in Asian and African nations first. The rate where the cancer patients increasing is so worrying, particularly in Bangladesh. The most popular form of liver cancer, hepatocellular carcinoma, or HCC affects more men than women. It has become a frequent condition in modern times. A growth called liver cancer forms in the liver tissue as a result of the liver cells' uncontrolled cell cycle. In this paper, we have explored the age prediction system for patients with hepatocellular carcinoma, a type of liver cancer. Based on the corresponding liver cancer diagnosis and other pertinent factors, we develop a neural network model which primarily focuses on the recognition of a certain age group.