Liver Disease Detection

In recent times, intelligent predictive systems are showing greater levels of accuracy and effectiveness in early detection the critical diseases cancer liver, lungs, etc. Predictive models assist medical practitioners to identify based on symptoms health indicators like hormones, enzymes, age, blood counts, This article focuses proposing an optimal classification model detect chronic liver disease by enhancing prediction through cutting-edge analytics. The proposes enhanced framework original study Ramana et al. It uses measures precision balanced choose most efficient algorithm Indian USA patient datasets using various factors Using Youden's index, individual thresholds for each were identified increase power sensitivity specificity, respectively. a highly accurate automated industry helps strategizing preventive patients.