Liver Disease Prediction using GA features selection, Social Spider Optimization and CNN Classification

Liver disease prediction is a critical task in healthcare, enabling early diagnosis and intervention to improve patient outcomes. In this study, we propose a novel approach integrating genetic algorithm (GA) feature selection, social spider optimization (SSO), and convolutional neural network (CNN) classification for accurate and efficient prediction of liver diseases.