Expert system supporting automatic risk classification and management in idiopathic membranous nephropathy based on rule sets and machine learning

Abstract

The diagnosis and management of idiopathic membranous nephropathy (IMN) is a complex clinical challenge due to the disease’s unpredictable progression and the varying responses to treatment. Traditional methods of risk stratification and treatment planning often rely on manual assessments, which can lead to inconsistent decision-making and suboptimal patient outcomes. To address this issue, we propose an expert system that leverages machine learning (ML) and artificial intelligence (AI) models and a knowledge-based approach to automate risk classification and treatment recommendations for IMN patients. This system aims to standardize and automate clinical decision-making, improve diagnostic accuracy, and enhance patient care through data-driven insights.