INFORMATION SYSTEM FOR EVALUATION OF THE STATE OF INTOXICATION OF THE ORGANISM BASED ON THE BAYES NETWORK
An expert system is a computer program that simulates the judgment and behavior of a human or an organization that has expert knowledge and experience in a particular field. It is a program that emulates the interaction a user might have with a human expert to solve a problem. The end user provides input by selecting one or more answers from a list or by entering data. An Expert System is a problem solving and decision making system based on knowledge of its task and logical rules or procedures for using knowledge. Both the knowledge and the logic are obtained from the experience of a specialist in the area. This paper considers approaches to building a knowledge base for medical systems. In developing the knowledge base of the information system, Bayesian networks were chosen as the basis for the decision-making model by type of patient pathology. This choice was due to the availability of these networks the ability to work with uncertain knowledge used in the diagnosis of diseases, in choosing the optimal course of treatment and subsequent prediction of patients. In addition, they offer the most adequate formal representation of inaccurate knowledge, as they are the result of a synthesis of statistical methods of data analysis and artificial intelligence. The presence of hydrosulfide ion intoxication (HS-intoxication), divalent iron ion intoxication (Fe-intoxication), the patient's absence of pathology and the value of Ag2S and Pt electrode potentials were selected as nodes of this network. Based on the accumulated experience of monitoring the condition of patients during their postoperative treatment (data obtained in collaboration with Ivano-Frankivsk National Medical University), as well as experimental data, conditional probabilities of values that can take the readings of the electrodes were established.
Experimental testing of the adequacy of the proposed and implemented model was performed on an array of data from potentiometric measurements of patients' biomaterial. The prediction made by the network was taken as the node that had the highest probability of being in a state that indicates the presence of a pathology. Comparison of the results of the network with data obtained by other methods showed their convergence in 85% of cases.
Thus, the developed network can be used to facilitate the process of diagnosing the presence and type of intoxication of the patient and is included in the information system for monitoring the patient's condition.
2. Mashevsky, G.А., & Tarasov, V.A. (2006) Rapid control of metal-ligand homeostasis disturbance during urine ionometry of patients with common forms of cancer. Bulletin of the State Electrotechnical University. Biotechnical systems in medicine and ecology. 2, 125–131.
3. Mashevsky, G.А. (2010). The system of monitoring the patient's condition in the postoperative period. Electronics in medicine. Monitoring, diagnosis, therapy, A, 527.
4. Mauno, V., & Samarghitean, C. (2008). Expert systems for medical applications. Medical Expert Systems Current Bioinformatics, Volume 3 , Issue 1.
5. Holman, J., & Cookson, M. J.(2009). Expert systems for medical applications. Journal of Medical Engineering & Technology , Volume 11, Issue 4.
6. Rahim, R., Purba, W., Khairani, M., Rosmawati, R. (2014) Online Expert System for Diagnosis Psychological Disorders Using Case-Based Reasoning Method. The 1st International Conference on Engineering and Applied Science,1381(2019).
7. Singla, J., Grover, H. D., Abhinav, М. (2014) Medical Expert Systems for Diagnosis of Various Diseases. International Journal of Computer Applications, Volume 93, 7, 36–43.
8. Imhanlahimi, R., John-Otumu, A.M. (2019) APPLICATION OF EXPERT SYSTEM FOR DIAGNOSING MEDICAL CONDITIONS: A METHODOLOGICAL REVIEW. European Journal of Computer Science and Information Technology,Vol.7, No.2, 12–25.
9. Liao, S.H. (2005). Expert system methodologies and applications-a decade review from 1995 to 2004. Expert Syst. Appl. 28, 93–103.
10. Kumar, Y, & Jain, Y. (2012). Research aspects of expert system. Int. J. Comput. Bus. Res. ISSN (Online): 2229–6166.
The authors who publish in this collection agree with the following terms:
• The authors reserve the right to authorship of their work and give the magazine the right to first publish this work under the terms of license CC BY-NC-ND 4.0 (with the Designation of Authorship - Non-Commercial - Without Derivatives 4.0 International), which allows others to freely distribute the published work with a mandatory reference to the authors of the original work and the first publication of the work in this magazine.
• Authors have the right to make independent extra-exclusive work agreements in the form in which they were published by this magazine (for example, posting work in an electronic repository of an institution or publishing as part of a monograph), provided that the link to the first publication of the work in this journal is maintained. .
• Journal policy allows and encourages the publication of manuscripts on the Internet (for example, in institutions' repositories or on personal websites), both before the publication of this manuscript and during its editorial work, as it contributes to the emergence of productive scientific discussion and positively affects the efficiency and dynamics of the citation of the published work (see The Effect of Open Access).