Abstract

The article proposes the principles for the development of a fuzzy rule-based physician decision support system n to determine the stages of the most common hepatocellular carcinoma (HCC) among malignant tumors of liver. The stages of HCC, i.e., critical situations, are expressed by different combinations of clinical signs of input data and emerging clinical conditions. These combinations shape the multiplicity of possible situations (critical situations) by forming linguistic rules that are in fuzzy relations with one another. The article presents the task of developing a fuzzy rules-based system for HCC staging by classifying the set of possible situations into given classes. In order to solve the problem, fuzzy rules of clinical situations and critical situations deviated from them are developed according to the possible clinical signs of input data. The rules in accordance with the decision-making process are developed in two phases. In the first phase, three input data are developed: nine rules are developed to determine possible clinical conditions based on the number, size, and vascular invasion of tumor. In the second phase, seven rules are developed based on possible combinations of input data on the presence of lymph nodes and metastases in these nine clinical conditions. At this stage, the rules representing the fuzzification of results obtained are also described. The latter provide an interpretation of results and a decision on related stage of HCC. It also proposes a functional scheme of fuzzy rules-based system for HCC staging, and presents the working principle of structural blocks. The fuzzy rule-based system for HCC staging can be used to support physicians to make diagnostic and treatment decisions

Highlights

  • Nowadays, the role of information technology in improving the quality of medical care provided to the population is undeniable, and the global development trend of electronic medicine (e-medicine) proves this

  • As one of these tools, the creation of intelligent systems based on the knowledge of experienced physicianexperts to support diagnostic and treatment decisions is on the agenda

  • Fuzzy rule-based systems (FRBS) was performed on Delphi programming platform for hepatocellular carcinoma (HCC) staging, and the software was implemented in the following stages: Database Development; KB Development; logical reasoning mechanism development

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Summary

Introduction

The role of information technology in improving the quality of medical care provided to the population is undeniable, and the global development trend of electronic medicine (e-medicine) proves this. One of the main fields of e-medicine is the development of Information and Communication Technologies (ICT) based tools to support physician decisions [1, 2] As one of these tools, the creation of intelligent systems based on the knowledge of experienced physicianexperts to support diagnostic and treatment decisions is on the agenda. The limited ability of the human brain to remember and judge the value of more than 7 indicators [7] leads to shortcomings in medical decisions determined by certain combinations of a large number of indicators These increase the need to develop intelligent systems that support physician to make error-free treatment and diagnostic decisions by comparatively analyzing large amounts of information in a complex, uncertain information environment

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