DECISION SUPPORT SYSTEM FOR THE HEPATOCELLULAR CARCINOMA DIAGNOSIS

Abstract

This article provides information on the architecture and implementation principles of the expert system for the diagnosis of hepatocellular carcinoma (HCC). The state of HCC is expressed by various combinations of possible values of its clinical signs, and the HCC staging is determined based on the classification of these combinations by given classes. The need to prevent medical errors due to large number, complexity, and quantitative and qualitative character of parameters referred to has made the development of the HCC diagnosis system urgent. This article presents an architecture of the system and its constituent knowledgebase, database, working principle of logical reasoning and interface blocks, and their mutual functional relationship. Based on the knowledge description production model, this study develops software realizing the mechanism of transforming the knowledge of doctors-experts into rules and forming a knowledge base, activating the appropriate rule from the knowledge base according to various combinations of input data, making a diagnostic decision and delivering it to a user. The diagnostic system implemented in C# programming language with web technologies is integrated on Visual Study 2019 platform. HCC staging system is tested and run online.