Liver Disease Data Classification Using Hypercube Optimization Search (HOS) Based Multilayer Perceptron (MLP) Model

Abstract

Liver cancer classification assumes an essential part in early detection and treatment planning. In this paper, we propose a Hypercube Optimization Search (HOS) based Multilayer Perceptron (MLP) model for compelling classification of liver cancer. The HOS algorithm is utilized to upgrade the MLP model's boundaries and work on its exhibition. A complete dataset of liver cancer patients is used for preparing and testing the proposed model. The trial results show that the HOS algorithm with MLP model accomplishes superior classification accuracy contrasted with customary methods. The proposed approach shows extraordinary potential in exact and productive liver cancer classification, thereby helping with opportune diagnosis and powerful treatment.