Category: Issue 4 (198)

Issue 4 (198), article 5

DOI:https://doi.org/10.15407/kvt198.04.078

Cybernetics and Computer Engineering, 2019, 4(198)

KOVALENKO A.S.¹, DSc (Medicine), Professor,
Head of the Medical Information Systems Department
e-mail: askov49@gmail.com

MISHCHENKO R.F., PhD (Medicine),
Physician,
e-mail: roman.mishchenko@gmail.com

KOZAK L.M., DSc (Biology), Senior Researcher,
Leading Researcher of the Medical Information Systems Department.
e-mail: lmkozak52@gmail.com

¹International Research and Training Centre for Information Technologies and Systems of the National Academy of Sciences of Ukraine and Ministry of Education and Science of Ukraine,
40, Acad. Glushkov av., Kyiv, 03187, Ukraine

²Khmelnytsky Regional Hospital,
1, Pilotska st., Khmelnytskyi, 29000, Ukraine

TRANSFORMATION OF CLINICAL DECISION SUPPORT SYSTEMS INTO FHIR STRUCTURES TO ENSURE QUALITY OF MEDICAL CARE

Introduction. The reform of the medical sector in Ukraine has given impetus to the development of eHealth and, as a consequence, the creation of medical registers systems and specialized medical information systems to support the operation of primary health care etc. One of the strategic directions of the health care system is to find and choose effective methods of managing the quality of care.

The purpose of the paper is to analyze the conditions and opportunities for transformation of the clinical decision support system using standard Fast Healthcare Interoperability Resources (FHIR) structures to ensure health care quality control.

Results. The current level of medical information systems development requires the application of the international standard FHIR, which are applied for the exchange of data between different systems of electronic medical records and between different components of the same electronic medical record (EMR) system, for standardization of interoperability.

Uninterrupted improvement model, known as the Plan-Do-Check-Act (PDCA), which consists of four components — planning, executing, testing and improving own process, is considered. The characteristics of the FHIR standard are analyzed and ways of transforming the clinical decision support system based on this standard are identified. The concept of an abstract data node, ensuring terminological compliance, implementation of the Workflow data model, and other functions and tasks of the clinical decision support system are described.

Conclusions. One of the important areas of eHealth development is to implement the information systems for care quality managing based on modern information medical standards. Creation and implementation of effective methods for monitoring (identifying) diagnostic and treatment quality in hospital will foster optimization and increase of their activity efficiency.

The use of the FHIR framework in the creation of information support system for evaluating the care quality enables to improve the data exchange quality and their processing for decision-making.

Keywords: eHealth, FHIR structures, clinical decision support system, health care quality control.

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REFERENCES

1 Hynes D.M., Perrin R.A, Rappaport S., Stevens J.M., Demakis J.G. Informatics Resources to Support Health Care Quality Improvement in the Veterans Health Administration. Journal of the American Medical Informatics Association. V.11, iss. 5. 2004, pp. 344-350. https://doi.org/10.1197/jamia.M1548

2 Campanella P., Lovato E., Marone C., Fallacara L., Mancuso A., Ricciardi W., Specchia M.L. The impact of electronic health records on health carequality: a systematic review and meta-analysis. European Journal of Public Health. 2016. V. 26, no 1, pp. 60-64. https://doi.org/10.1093/eurpub/ckv122.
https://doi.org/10.1093/eurpub/ckv122

3 Heller B., Kruger M., Loffler M., Mantovani L., Meineke F., Mishchenko R. OncoWorkstation – Ein adaptives Agentensystem fur das Therapiemanagement klinischer Studien. 2002, Berlin.

4 Meineke, F., Mishchenko, R., Mantovani, L., Loffler, M. & Heller, B. Onco-Workstation – ein Konsultations- und Planungswerkzeug zur Unterstutzung der Auswahl und Durchfuhrung von onkologischen Therapiestudien. In: Jahrestagung der GMDS. Informatik, Biometrie und Epidemiologie in Medizin und Biologie, 2003.

5 Voronenko Yu., Gorachuk V. Management of quality of medical care: world and domestic models. Eastern European Journal of Public Health. 2012, no. 2-3 (18-19), pp. 64-67. (in Ukranian)

6 Voronenko Yu., Gorachuk V. Methodical approaches to implementation of standardization of organizational technologies in the quality management system of medical care. Ukrainian Medical Journal. 2012, no. 5(91), pp. 108-110. (in Ukranian)

7 Gorachuk V., Bogatir I. Experience in the development and implementation of an information system for monitoring the quality of care. Medical Forum. 2014. no 2. P. 55-59. (in Ukranian)

8 Kovalenko O.S., Kozak L.M., Romanyuk O.A. Digital Medicine Information Technology. Kibernetika i vycislitelnaa tehnika. 2017, 1(187), pp. 69-79. (in Russian) https://doi.org/10.15407/kvt187.01.067

9 Rogozinskaya N.S., Kozak L.M. Information support of technology for automated monitoring of the state of public health. Kibernetika i sistemnyj analiz, 2013, no. 6, pp. 162-173. https://doi.org/10.1007/s10559-013-9585-1

10 Kozak L.M., Kovalenko O.S., Romanyuk O.A, Antomonov M.Yu. Formation of Information Medical Environment in Different Levels. Proc. SPIE. 11176, Photonics Applications in Astronomy, Communications, Industry, and High-Energy Physics Experiments. 2019, 6 November 2019. https://doi.org/10.1117/12.2536412

11 Impact of Heath Information Technology on the Quality of Patient Care. OJNI. V. 19. 2015.

12 Kozak L.M., Kovalenko A.S., Kryvova O.A., Romanyuk O.A. Digital Transformation in Medicine: From Formalized Medical Documents to Information Technologies of Digital Medicine. Kibernetika i vycislitelnaa tehnika. 2018. no. 4(194). P. 61-78. https://doi.org/10.15407/kvt194.04.061

13 Ross D. S., Venkatesh R. Role of Hospital Information Systems in Improving Healthcare Quality in Hospitals. Indian Journal of Science and Technology. 2016. v. 9(26). P.1-5. https://doi.org/10.17485/ijst/2016/v9i26/92686

14 Crosson J.C., Stroebel C., Scott J.G., Stello B., Crabtree B.F. Implementing an Electronic Medical Record in a Family Medicine Practice: Communication, Decision Making, and Conflict.Annals of Family Medicine. 2005. Vol. 3. no. 4. P. 7-11. https://doi.org/10.1370/afm.326

15 Coiera E., Westbrook J.I., Wyatt J.C. The Safety and Quality of Decision Support Systems. URL: https://www.researchgate.net/publication/6745100 (Last accessed: 05.09.2019.)

16 HL7 Messaging Standard Version 2.7. URL: http://www.hl7.org/ implement/standards/product_brief.cfm?product_id?146. (Last accessed: 01.09.2018).

17 Mandel J.C., Kreda D.A., Mandl K.D., Kohane I.S., Ramoni R.B. SMART on FHIR: a standards-based, interoperableappsplatformforelectronichealthrecords. Journal of the American Medical Informatics Association Advance Access. 2016. P.1-10.

18 Version History since DSTU #1 URL: https://build.fhir.org/history.htm (Last accessed:08.08.2019.)

19 How FHIR works and what’s a FHIR resource.URL: https://searchhealthit.techtarget.com/definition/FHIR-Fast-Healthcare-Interoperability-Resources (Last accessed: 08.08.2019.)

20 Bender D, Sartipi K. HL7 FHIR: anagile and REST ful approach to health care information exchange. In IEEE 26th International Symposiumon Computer-Based Medical Systems (CBMS). 2013. P. 326-331. https://doi.org/10.1109/CBMS.2013.6627810

21 Zhemchugov A.M., Zhemchugov M.K. PDCA Deming cycle. Modern development. Problems of economy and management. 2016. no. 2 (54). P.3-28. (in Russian)

Received 21.08.2019

Issue 4 (198), article 4

DOI:https://doi.org/10.15407/kvt198.04.062

Cybernetics and Computer Engineering, 2019, 4(198)

VOVK М.І., PhD (Biology), Senior Researcher,
Head of Bioelectrical Control & Medical Cybernetics Department
e-mail: vovk@irtc.org.ua; imvovk3940@gmail.com

KUTSYAK О.А., PhD (Engineering),
Senior Researcher of Bioelectrical Control & Medical Cybernetics Department
e-mail: spirotech85@ukr.net

International Research and Training Center for Information Technologies and Systems of the National Academy of Sciences of Ukraine and of Ministry of Education and Science of Ukraine,
40, Acad. Glushkov av., Kyiv, 03187, Ukraine

SOFTWARE MODULE FOR PERSONAL DIAGNOSTICS OF MOTOR FUNCTIONS AFTER STROKE

Introduction. Diagnostics of motor functions after stroke plays an important role in the formation of a rehabilitation program. The results of the preliminary clinical trials of our proposed technique for quantitative assessment of motor functions deficit during studying the dynamics of movement restoring based on bio-informational technology of motor control TRENAR® confirmed the advisability of using this technique to create a new algorithmic and software tools for personal diagnostics of motor functions.

The purpose of the paper is to develop a specialized module for the personal diagnostics of motor functions in patients after stroke, which software implements the determination of the degree of motor functions disorders and the results of their recovery using the technique for quantitative assessment of motor functions deficit.

Results. The structural and functional model of the software module for personal diagnostics of motor functions and the effectiveness of their recovery as a result of rehabilitation measures in patients after stroke has been developed.

An algorithm for diagnostic the motor functions disorder degree of the affected limbs in patients after stroke and the activity diagram of software module using Unified Modeling Language (UML) are presented. The software module “Movement Test Stroke” has been made in Visual Studio 2013 software environment. The programming language is C#. The module is installed in the PC structure. Diagnostic benefits: the ability to obtain an integrated quantitative assessment of the motor functions deficit of the upper and lower limb at the level of separate joints, hand or walking according to relevant evidential criteria, and assessment of muscle hyper- or hypotone at different stages of rehabilitation. The advantage of diagnostics is that the motor func functions disorder degree is performed relative to the patient’s own healthy limbs, the motor functions of which characterize the individual norm of disorders absence.

Conclusions. The quantitative assessment of motor function deficit by evidential criteria, which is provided by the software module “Movement Test Stroke” is the basis to synthesize the digital health mobile means for information and advisory assistance to the physician in creating and making adjustments to personal plan for recovery the motor functions affected by pathology at different stages of stroke rehabilitation.

Keywords: software module, structural and functional model, diagnostics, algorithm, motor functions, personal quantitative assessment, stroke.

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REFERENCES

1 Action Plan for Stroke in Europe 2018-2030 / Bo Norrving et al. European Stroke Journal. 2018. Vol. 3(4). P. 309-336. https://doi.org/10.1177/2396987318808719

2 Gritsenko V.I., Vovk M.I. Trenar – Innovative Technology of Restoration of Movements. In Materials of the International Scientific and Practical Forum “Science and Business – the basis of economic development”. Dnipro, 2012. P. 204-206. (in Russian).

3 Vovk M.I. Information Technology of Movement Control. Evolution of Synthesis and Development Prospects. Kibernetika i vycislitelnaa tehnika. 2018. No 4 (194). P. 79-97. (in Ukrainian). https://doi.org/10.15407/kvt194.04.079

4 Vovk M.I., Kutsiak O.A., Lauta A.D., Ovcharenko M.A. Information Support of Researches on the Dynamics of Movement Restoration After the Stroke. Kibernetika i vycislitelnaa tehnika. 2017. No 3 (189). P. 61-78. (in Ukrainian). https://doi.org/10.15407/kvt189.03.061

5 Belova A., Shchepetova O. Scales, tests and questionnaires in medical rehabilitation. Moscow, 2002. (in Russian).

6 Kadykov A., Chernikova L., Shahparonova N. Rehabilitation of neurological patients. Moscow, 2008. (in Russian).

7 Smychek V., Ponomareva E. Craniocerebral trauma (clinic, treatment, examination, rehabilitation). Minsk, 2010. (in Russian).

8 Buch G., Rambo D., Yakobson I. The language of the UML. User’s Guide. Moscow, 2006. (in Russian).

9 Theory and practice of UML. Activity diagram. URL: http://it-gost.ru/articles/view_articles/96 (Last accessed: 04.06.2019). (in Russian).

Received 07.08.2019

Issue 4 (198), article 3

DOI:https://doi.org/10.15407/kvt198.04.040

Cybernetics and Computer Engineering, 2019, 4(198)

CHIKRII G.Ts., DSc. (Phys-Math), Senior Researcher
Leading Researcher of the Economical Cybernetics Department
e-mail: g.chikrii@gmail.com

V.M. Glushkov Institute of Cybernetics of the National Academy of Sciences of Ukraine
40, Acad. Glushkov av., Kyiv, 03187, Ukraine

PRINCIPLE OF TIME STRETCHING IN GAME DYNAMIC PROBLEMS

Introduction. There exists a wide range of mechanical, economical and biological processes evolving in condition of conflict and uncertainty, which can be described by various kind dynamic systems, depending on the process nature. This paper deals with the dynamic games of pursuit, described by a system of general form, encompassing a wide range of the functional-differential systems. The deciding factor in study of dynamic games is availability of information on current state of the process. In real systems information, as a rule, arrives with delay in time. Also, there are a number of problems for which Pontryagin’s condition, reflecting an advantage of the pursuer over the evader in control resources, does not hold. Establishment of close relation between its time-stretching generalization and the effect of variable information delay offers much promise for solving above mentioned problems.

The purpose of the paper is, to establish sufficient conditions for termination of the games on the basis of effect of information delay, for which Pontryagin’s condition does not hold, to specify these conditions for the case of integro-differential dynamics, and to illustrate the obtained result with the model example.

Methods. For investigation of the dynamic game of pursuit we apply the scheme of Pontryagin’s First Direct Method providing bringing of the trajectory of conflict-controlled process to the cylindrical terminal set at a finite moment of time. In so doing, construction of the pursuer’s control is accomplished on the basis of the Filippov-Castaing theorem on measurable choice insures realization of the process of pursuit in the class of stroboscopic strategies by Hajek. To deduce solution of the conflict-controlled integro-differentional system in the form of Cauchy formula, the method of successive approximation is used.

Results. It is shown that the dynamic game of pursuit with separated control blocks of the players and variable delay of information is equivalent to certain perfect information game. Based on this fact, the principle of time stretching is developed to study the games with complete information for which classic Pontryagin’s condition, lying at the heart of all direct methods of pursuit, does not hold. The time-stretching modification of this condition, proposed in the paper, makes it feasible to obtain sufficient conditions for bringing the game trajectory to the terminal set at a finite moment of time. In so doing, the control of pursuer, providing achievement of the game goal, is constructed. These conditions are specified for the integro-diffential game of pursuit. By way of illustration, an example of integro-differential game of pursuit is analyzed in detail. It is found that the time stretching function provides fulfillment of generalized Pontryagin’s condition. Simple relationships between dynamics parameters and control resources of the players are deduced that provide capture of the evader by the pursuer, under arbitrary initial states of the players.

Conclusion. Thus, in the paper an efficient tool is developed for analysis of conflict situation, for example, interception of a mobile target by controlled object in condition of conflict counteraction. Situation is analyzed, when the pursuing object lacks conventional advantage in control resources over the evading counterpart, that is, the classic Pontryagin’s condition does not hold. Suggested approach makes it feasible to realize the process of pursuit with the help of appropriate Krasovskii’ counter-controls.

Keywords: dynamic game, time-variable information delay, Pontryagin’s condition, Aumann’s integral, principle of time stretching, Minkowski’ difference, integro-differential game.

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REFERENCES

1 Isaacs R. Differential Games. Moscow, 1967. (in Russian).

2 Pontryagin L.S. Selected Scientific Papers. Vol. 2. Moscow, 1988. (in Russian).

3 Krasovskii N.N. Game Problems on the Encounter of Motions. Moscow, 1970. (in Russian).

4 Berkovitz L.D. Differential games of generalized pursuit and evasion. SIAM Control and Optimization. 1986. Vol. 24. No 3. P. 361-373. https://doi.org/10.1137/0324021

5 Friedman A. Differential Games. New York, 1971.

6 Hajek O. Pursuit Games. New York, 1975.

7 Pshenitchny B.N. -strategies in Differential Games, Topics in Differential Games. New York, London, Amsterdam: North Holland, 1973. P. 45-99.

8 Chikrii A.A. An analytic method in dynamic games. Proceedings of the Steklov Institute of Mathematics. 2010. Vol. 271. P. 69-85. https://doi.org/10.1134/S0081543810040073

9 Dziubenko K.G., Chikrii A.A. An approach problem for a discrete system with random perturbations. Cybernetics an York, Sprid Systems Analysis. 2010. Vol. 46. No.2. P. 271-281. https://doi.org/10.1007/s10559-010-9204-3

10 Dziubenko K.G., Chikrii A.A. On the game problem of searching moving objects for the model of semi-markovian type. Journal of Automation and Information Sciences. 2006. Vol. 38. No.9. P. 1-11.

11 Siouris G. Missile Guidance and Control Systems. New York, 2004. https://doi.org/10.1115/1.1849174

12 Chikrii G.Ts. On a problem of pursuit under variable information time lag on the availability of a state vector. Dokl. Akad. Nauk Ukrainy. 1979. No. 10. P. 855-857 (in Russian)

13 Chikrii G.Ts. An approach to solution of linear differential games with variable information delay. J. Autom. and Inform. Sci., 1995. Vol. 27 (3&4). P. 163-170.

14 Nikolskij M.S. Application of the first direct method in the linear differential games. Izvestia Akad. Nauk SSSR. Vol 10:51-56 (in Russian).

15 Chikrii A.A. Conflict-Controlled Processes. Springer Science & Business Media, 2013.

16 Mezentsev A.V. On some class of differential games. Izvestia AN SSSR. Techn. kib. 1971. No. 6. P.3-7 (in Russian).

17 Zonnevend D. On One Method of Pursuit. Doklady Akademii Nauk SSSR. Vol. 204. P. 1296-1299 (in Russian).

18 Chikrii G.Ts. Using impact of information delay for solution of game problems of pursuit. Dopovidi Natsional’noi Akademii Nauk Ukrainy. Vol 12. P. 107-111.

19 Chikrii G.Ts. One approach to solution of complex game problems for some quasilinear evolutionary systems. Journal of Mathematics, Game Theory and Algebra. 2004. Vol. 14. P. 307-314.

20 Chikrii G.Ts. Using the effect of information delay in differential pursuit games. Cybernetics and Systems Analysis. 2007. Vol. 43. No. 2. P. 233-245. https://doi.org/10.1007/s10559-007-0042-x

21 Chikrii G.Ts. On one problem of approach for damped oscillations. Journal of Automation and Information Sciences. 2009. Vol. 41. No.4. P. 1-9. https://doi.org/10.1615/JAutomatInfScien.v41.i10.10

22 Chikrii G.Ts. Principle of time sretching in evolutionary games of approach. Journal of Automation and Information Sciences. 2016. Vol.48. No. 5. P. 12-26. https://doi.org/10.1615/JAutomatInfScien.v48.i5.20

23 Aumann R.J. Integrals of set-valued functions. J. Math. Anal. Appl. 1965. vol.12. P. 1-12 https://doi.org/10.1016/0022-247X(65)90049-1

24 Filippov A.F. Differential Equations with Discontinuous Right Side. Moscow, 1985 (in Russian).

25 Krasnov M.L., Kiseliov A.I., Makarenko G.I. Integral Equations. Moscow. 1968. (in Russian).

26 Kolmogorov A.N., Fomin S.V. Elements of Theory of Functions and Functional Analysis. Moscow, 1989. (in Russian).

Received 04.09.2019

Issue 4 (198), article 2

DOI:https://doi.org/10.15407/kvt198.04.026

Cybernetics and Computer Engineering, 2019, 4(198)

TOKOVA O.V.,
Junior Researcher of the Department of Information Technologies for Inductive Modeling
e-mail: len327@ukr.net

SAVCHENKO Ye.A., PhD (Engineering),
Senior Researcher of the Department of Information Technologies for Inductive Modeling
e-mail: savchenko_e@meta.ua

STEPASHKO V.S., DSc (Engineering), Professor,
Head of the Department of Information Technologies for Inductive Modeling
e-mail: stepashko@irtc.org.ua

International Research and Training Center for Information Technologies
and Systems of the National Academy of Sciences of Ukraine
and Ministry of Education and Science of Ukraine,
40, Acad. Glushkov av., Kyiv, 03187, Ukraine

CONSTRUCTION OF A COMPUTER TECHNOLOGY FOR INFORMATION SUPPORT OF DECISIONS IN THE FOUNDRY PRODUCTION PROCESS

Introduction. To ensure the high-quality manufacture of foundry products, advanced computer technologies are required which would contain not only a database of metals and alloys but also information on defect formation processes and methods for producing castings of a given quality. Software development requires detailed analysis not only of existing advanced technologies, but also the needs of the customer, compliance with all stages of the technological process, determination of the production profile.

The purpose of the paper is to analyze existing approaches and tools used in the foundry support industry to develop a computer technology containing a database of Ukrainian standards and specifications and providing guidance on the tasks involved in the casting process. To construct such technology for supporting the foundry making in the casting process, it is necessary to identify the advantages and disadvantages of existing facilities, assess the feasibility of using these tools in the domestic production and formulate requirements for computer technology developed in accordance with specifics of the Ukrainian foundries and oriented to work with the domestic base of metals and alloys.

Results. The analysis of modern software for computer modeling of processes in the field of formation of metals and alloys is carried out. It is planned to use the results of the analysis when creating a computer technology for modeling thermal processes in the field of foundry production focused on the Ukrainian industry to simplify the casting process. This will increase the production volume and reduce the appearance of defects in casting products during the technological process to make them more competitive. The block diagram of the computer technology of information support for decision-making in the foundry process is given. The main blocks of this system and the tasks they will solve are described.

Conclusions. An analysis of modern software for computer simulation of processes in the field of metal molding and the methods which are the basis of software products is executed. The results of the analysis are used when creating the computer technology of simulation of the thermal processes in the field of foundry, which will be oriented on Ukrainian industries, simplify the process of the casting obtaining. This will result in an increase of the production volume and reduce the appearance of defects in casting products during technological process to make them more competitive.

Keywords: casting, foundry production, computer technology, information support of decisions, group method of data handling (GMDH).

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REFERENCES

1 Mehta N.D., Gohil A.V., Sachindra, Doshi J. Innovative Support System for Casting Defect Analysis – A Need of Time. Materials Today: Proceedings. Vol. 5. Issue 2. Part 1. 2018. P. 4156-4161. https://doi.org/10.1016/j.matpr.2017.11.677

2 Gumann M., Sholapurwalla A. Investment Casting Simulation. URL: https://www.esi-roup.com/sites/default/files/resource/publication/1704/t_investmentcasting.pdf. (Last accessed: 06.05.2017).

3 Kravchenko O.V., Savchenko Ye.A. Information technology of inductive modeling of casting process monitoring. Inductive modeling of complex systems. Kyiv: IRTC ITS. 2015. P. 140-146 (In Ukranian)

4 Tokova O.V., Savchenko Ye.A. Approach to the development of information support solutions for foundry production. Inductive modeling of complex systems. Kyiv: IRTC ITS. 2016. P. 194-202 (In Ukranian)

5 Zhiganov N.K., Fomina E.E. Program for modeling the process of continuous casting of non-ferrous metals and their alloys. Software products and systems. 2008. No. 1. P. 10-12.

6 URL: https://www.magmasoft.de/en/ (Last accessed: 02.10.2019).

7 URL: http://www.afsinc.org/news/AFSNewsList.cfm?Yr=2016 (Last accessed: 13.04.2016 ).

8 Roshan H. Process knowledge in foundries.URL: https://cdn2.hubspot.net/hubfs/

9 237924/Processknowledge-DrRoshan-Jan31-2012.pdf (Last accessed: 12.11.2018.)

10 Thoguluva R.V., Piccardo P. Computers in Foundries. Metallurgical Science and Technology. Vol. 30-2 Ed. 2012. P. 28-38.

11 Kaufman J.G., Rooy E.L. Aluminum Alloy Castings: Properties, Processes and Applications. ASM International. 2004. 340 p.

12 Tarasevich N.I., Korniec I.V., Tarasevich I.N., Dudchenko A.V. Comparative analysis of computer simulation systems for metallurgical and casting processes. Metal and casting of Ukraine. No. 5. 2010. P. 20-25. (In Russian).

13 Matthias Gaumann, Adi Sholapurwalla Investment casting simulation URL: https://pdfs.semanticscholar.org/73e4/a68d4ad01a8c76bda9489da69e97508402ec.pdf (Last accessed: 12.11.2018.)

14 Anton V.A., Balaykin A.V., Smelov VG., Agapovichev A.V. Application of Additive Technologies in the Production of Aircraft Engine Parts. Modern Applied Science. Vol. 9. No. 4. 2015. P. 151-159. https://doi.org/10.5539/mas.v9n4p151

15 Dudchenko A.V. Evolutionary development of computer modeling systems for foundry processes at “NMBP”. Compliance with the requirements of the time. (Kramatorsk, 30th of Sept – 4th of Oct. 2013). Kramatorsk, on “NMBP”, 2013. P. 97-98. (In Russian).

16 URL: http://uas.su/books/spesialmethodsforcasting/1/razdel1.php. (Last accessed: 01.11.2018.)

17 Treyger, P.E. Overview of Foundry Processes and Technologies: Manufacturing Metal Castings. URL: https://www.cedengineering.com/userfiles/Castings.pdf. (Last accessed: 01.11.2018.)

18 Tokova O., Savchenko Ye. Inductive Modelling as a Basis of Informational Support of Decisions in Casting Production. Proceedings of the XII IEEE International Conference CSIT-2017 & International Workshop on Inductive Modeling (Lviv, 5th – 8th of Sept., 2017). Lviv, 2017. P. 507-510. https://doi.org/10.1109/STC-CSIT.2017.8098838

19 Savchenko, Ye.A., Kravchenko, O.V. Application of the inductive approach for simulation of the cooling process of casting according to experimental data. Inductive modeling of complex systems. Collected research papers. Issue 6. Kyiv: IRTC ITS NASU. 2014. P. 126-136. (In Ukranian)

20 Savchenko, Ye.A., Stepashko V.S., Tokova O.V. The construction task for a decision support system in foundry industry. Proceedings of XXIV International Conference of Automatica-2017. (Kyiv, 13th – 15th of Sept. 2017). Kyiv, 2017. 196 p. (In Ukranian)

21 Tokova O.V. The task of the computer technology construction for thermal processes modeling of foundry production. Upr. sist. mas. 2018. 4 (276). P. 84-95. (In Ukranian) https://doi.org/10.15407/usim.2018.04.084

Received 27.09.2019

Issue 4 (198), article 1

DOI:https://doi.org/10.15407/kvt198.04.003

Cybernetics and Computer Engineering, 2019, 4(198)

PEROVA I.G., PhD (Engineering), Associate Professor
Associate Professor of Biomedical Engineering Department,
e-mail: rikywenok@gmail.com

BODYANSKIY Ye.V., DSc (Engineering), Professor
Professor of Artificial Intelligence Department
e-mail: yevgeniy.bodyanskiy@nure.ua

Kharkiv National University of Radio Electronics,
14, Nauky av., Kharkiv, 61166, Ukraine.

ONLINE MEDICAL DATA STREAM MINING BASED ON ADAPTIVE NEURO-FUZZY APPROACHES

Introduction. Data mining approaches in medical diagnostics tasks have a number of special properties that do not allow the use of such approaches in a classical form. That’s why adaptive neuro-fuzzy systems for online medical data stream processing tasks and its learning algorithms have been developed. Proposed systems can process medical data streams in three modes: supervised learning, unsupervised learning and active learning.

The purpose of the paper is to develop approach, based on adaptive neuro-fuzzy systems to solve the tasks of medical data stream mining in online-mode.

Methods. The methods of computational intelligence are used for medical data stream processing and, first of all, artificial neural networks, neuro-fuzzy systems, neo-fuzzy systems, their supervised, unsupervised and active learning approaches, gradient methods of optimization, methods of evolving system.

Results. As a result, approbation of the developed approach in supervised learning mode using multidimensional neo-fuzzy neuron on medical data of patients with urological disease was investigated. Percentage of errors in system testing using all feature space is 11.11 %, using the most informative features the error rate becomes 6.4 %. Also multidimensional neo-fuzzy neuron was used for diagnostic of the pharmacoresistant form of epilepsy, percentage of errors in system testing is 5.82 %. Approval of the developed approach in the mode of active training and association on the data of patients with pulmonary diseases was performed. For all approbation results performance criterion was calculated, its values are suitable for the tasks of medical diagnostics in data stream mode.

Conclusions. The proposed neuro-fuzzy approaches allow obtaining additional information about patients’ diagnosis in conditions of limited a priori information about patient.

Keywords: adaptive system, neuro-fuzzy system, medical data mining, medical data stream.

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Received 10.07.2019