№1, 2021

PRINCIPLES FOR THE DEVELOPMENT OF AN INTELLIGENT HEPATOCELLULAR CARCINOMA STAGING SYSTEM

Masuma G. Mammadova, Nuru Y. Bayramov, Zarifa G. Jabrayilova, Minara I. Manafli, Mehriban R. Huseynova

The article proposes the principles of developing a support system for the adoption of medical decisions for determining the stages of hepatocellular carcinoma (HCC), which is the most common among malignant liver tumors. HCC is characterized by a set of clinical manifestations of critical conditions, each of which, in turn, is determined by a variety of clinical signs. Specific clinical manifestations of the state of HCC are expressed by various combinations of the values of the signs, which determine the multivariance of possible situations. Establishment of the stages of HCC requires a classification of many possible situations according to given classes and is the basis for choosing a treatment regimen for the disease. In conditions of multivariate situations in order to prevent possible medical errors, the task of developing an intelligent system for determining the stages of HCC is set. In accordance with the methodological approach to the development of intelligent systems, a conceptual model of the problem of determining the stages of HCC is proposed, the basic concepts and their relationship are determined. To transform the obtained expert knowledge into a system, a production model of knowledge representation is used, rules that form the knowledge base are developed. The structure of the computer system for determining the stages of HCC is developed, the principles of operation of its constituent blocks are shown. The working windows of the system implemented on the Delphi software platform are presented, the decision-making mechanism is described. An intelligent system developed to determine the stages of HCC can be used as a computer assistant for a doctor in the process of diagnostic and treatment decisions (pp.3-14).

Keywords: the stages of hepatocellular carcinoma, intelligent system, knowledge base, production model, rules, decision making.
DOI : 10.25045/jpit.v12.i1.01
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