MATHEMATICAL SUPPORT OF THE INTELLIGENT INFORMATION SYSTEM OF ASSESSING THE OBJECT STATE
DOI:
https://doi.org/10.30837/2522-9818.2017.2.093Keywords:
mathematical support, information system, myocardial infarction, prediction modelAbstract
At present, information technologies (IT) are intensively used all over the world in various sectors, and today medical institutions cannot do without them when organizing the process of medical diagnostic. The IT efficiency is determined by the degree of their intellectualization that is by including knowledge bases as their component and by the transition from data processing to the processing of knowledge. The efficiency of making decisions in various areas of activity is determined by the quality and quick delivery of information. Medicine constitutes no exception in this sense. The advanced level of computer technology, applied tools, diagnostics on the basis of automated systems of decision support made it possible to solve the tasks of assessing the state of the object at a qualitatively new level. The subject matter of this study is to ensure the mathematical support of the intelligent information system (IS) of assessing the state of the object. The object is understood as a patient who came through a myocardial infarction (MI). The goal of the study is to develop mathematical support of the intelligent IS of assessing and predicting a patient’s condition. To achieve the stated goal, the following tasks were solved: statistically valid and uncorrelated signs were specified; these signs enable distinguishing the group of patients who survived from those who died, “decisive rules” were formulated for predicting the MI clinical outcome. In the process of the study, the mathematical IT of assessing the state of the object was developed. The following result was obtained: the suggested mathematical models for predicting the outcome of myocardial infarction that were developed with the use of the method of discriminant function and took into account human blood values can prevent sudden coronary death and improve the diagnostic efficiency. Conclusions. Mathematical models were developed to predict the state of the object in the event of uncertainty. The use of the developed mathematical models enables improving the accuracy of predicting the state of the object in a real-time environment and in the early stages of the disease development by 4.2% and 10%, and applying adequate preventive and therapeutic and rehabilitation measures in time as well as preventing sudden coronary death. The developed mathematical models were tested.
References
Timofeev, V. A., Hutsa, O. N., Shcherbyna, E. A. (2015), "Information technology of synthesis and analysis of functional models of interactive regulations" ["Ynformatsyonnaia tekhnolohyia syntezay analyza funktsyonalnykh modelei ynteraktyvn ykh rehlamentov"]. Bulletin of NTU" KhPI". Series: Strategic management, portfolio, program and project management. No. 55 (1097). P. 45-51.
Timofeev, V. O., Danylchenko, V. M., Kyrii, V. V. (2017), "The current state and trends of the development of quality management systems for data transmission in information systems" ["Suchasnyi stan ta tendentsii rozvytku system upravlinnia yakistiu peredachi danykh v informatsiinykh systemakh"]. Matematychni modeli ta novitni tekhnolohii upravlinnia ekonomichnymy ta tekhnichnymy systemamy. Kharkiv: FOP Mezona V. V. P. 268-275.
Timofeev, V. O., Hutsa, O. M., Peresada, O. V. (2017), "Information technology for creation of expert bot on the basis of procedural knowledge" ["Informatsiina tekhnolohiia stvorennia botiv-ekspertiv na osnovi protseduralnykh znan"]. Bulletin of NTU" KhPI". Series: System Analysis, Control and Information Technologies. No. 2 (1224). P. 23-28.
Timofeev, V. O., Kharchenko, V. S., Andrashov, A. O., Skliar, V. V., Siora, O. A. (2012), "Gap-and-IMECA-Based Assessment of I&C Systems Cyber Security". Complex Systems and Dependability: Springer-Verlag Berlin Heidelberg, Advances in intelligent and soft computing. No. 170. P. 149-164.
Timofeev, V. A., Samer, L. (2009), "About one approach to the synthesis of a dynamic object management system" ["Ob odnom podkhode k syntezu system y upravlenyia dynamycheskym objektom"]. Suchasni informatsiini tekhnolohii v ekonomitsi ta upravlinni pidpryiemstvamy, prohramamy ta proektamy. Kharkiv: KhAY. P. 249-250.
Timofeev, V. O. (2011), "Mathematical models of economic monitoring in conditions of uncertainty" ["Matematychni modeli ekonomichnoho monitorynhu za umov nevyznachenosti"]. Kharkiv. KhNURE. р. 102.
Timofeev, V.A., Udovenko, S.H. (2005), "Analysis of identification algorithms for noisy results of observations" ["Analyz alhorytmov identyfykatsyy pry zashumlennykh rezultatakh nabliudenyi"]. Vestnyk KhNTU. Kherson. No. 1 (21). P. 31-38.
Vysotskaya, E. V., Strashnenko, A. N., Demin, Y. A., Prasol, I. V., Sinenko, C. A. (2013), "A method for prognosis of primary open-angle glaucoma". International Review on Computers and Software. Vol. 8. Issue 8. P. 1943-1949.
Vуsotska, O., Dobrorodnia, М., Gordiyenko, М., Klymenko, V., Chovpan, A., Georgiyants, М. (2016), "Studying the mechanisms of formation and development of overweight and obesity for information system diagnostic of obesity". Eastern-European Journal of Enterprise Technologies. No. 6/2 (84). P. 15-23. Available at: http://journals.uran.ua/eejet/article/view/85390
Bespalov, Y. G., Nosov, K. V., Vysotska, O., Porvan, A. P., Omiotek, Z., Burlibay, A., Assembay, A., Szatkowska, M. (2017), "Mathematical modeling of systemic factors determining the risk of deterioration of drinking water supply and development of allergic diseases of population". Proc. SPIE 10445. Photonics Applications in Astronomy, Communications, Industry, and High Energy Physics Experiments. 104453K (7 August). DOI: 10.1117/12.2280964
Vysotskaya, E. V. Pecherskaya, A. Y., Dovnar, A. Y. (2014), "Making medical decisions in conditions of uncertainty" ["Pryniatye medytsynskykh reshenyi v uslovyiakh neopredelennosty"]. Eastern-European Journal of Enterprise Technologies. Vol. 3. No. 4 (69). P. 16-21.
Wójcik, W., Vуsotska, O., Klymenko, V., Trubitcin, A., Pecherska, A., Savchuk, T., Kolimoldayev, M., Szatkowska, M., Burlibay, A., (2017), "Risk assessment of bronchial asthma development in children with atopic dermatitis", Proc. SPIE. 10445, Photonics Applications in Astronomy, Communications, Industry, and High Energy Physics Experiments.
Yakubovska, S. V. Vуsotska, O., Porvan, A., Yelchaninov, D., Linnyk E. (2016), "Developing A Method For Prediction Of Relapsing Myocardial Infarction Based On Interpolation Diagnostic". Eastern-European Journal of Enterprise Technologies: Information and controlling system. Vol. 5. No. 9 (83). P. 41-49. Available at: http://journals.uran.ua/eejet/article/view/81004
Yakubovska, S. V., Nikonov, V. V., Porvan, A. P., Dovnar, A. Y., Chyzhyk, E. Y (2016), "The automated system of the outcome of myocardial infarction" ["Avtomatyzyrovannaia systema iskhoda infarkta miokarda"]. Bulletin of NTU" KhPI". Series: "Mechanic-technological systems and complexes". No. 49. P. 58-62.
Dziak, H. V., Kolesnyk, T. V., Bulanaia, T. M., Ehorov, K. Iu. (2009), "Information technology of dynamic monitoring for diagnosis of cardiovascular diseases" ["Informatsyonnaia tekhnolohyia dynamycheskoho monytorynha dlia dyahnostyky serdechno-sosudystykh zabolevanyi"]. Clinical Informatics and Telemedicine. Vol. 5. No. 6. P. 52-57.
Melnyk, K. V., Holoskokov, A. E. (2008), "The procedure for diagnosing the patient's cardiovascular system condition based on fuzzy logic" ["Protsedura dyahnostyrovanyia sostoianyia serdechno-sosudystoi systemy patsyenta na osnove nechetkoi lohyky"]. Bulletin of NTU" KhPI". Series: "Information and Modeling". No. 49. P. 101-104.
Dubrova, T. A. (2005), Statistical methods of forecasting [Statystycheskye metody prohnozyrovanyia]. Moscow: Yunyta-Dana. 206 p.
Petry, A., Sabyn, K. (2009), Visible medical statistics [Nahliadnaia medytsynskaia statistika]. Moscow: HIAOTAR-Medya. 168 p.
Medyk, V. A., Tukmachev, M. S. (2007), Mathematical statistics in medicine [Matematycheskaia statystyka v medytsyne]. Moscow: Fynansi i statistika. 800 p.
Downloads
How to Cite
Issue
Section
License
Copyright (c) 2018 Sofiia Yakubovska, Olena Vysotska, Vladimir Timofeev
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
Our journal abides by the Creative Commons copyright rights and permissions for open access journals.
Authors who publish with this journal agree to the following terms:
Authors hold the copyright without restrictions and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License (CC BY-NC-SA 4.0) that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this journal.
Authors are able to enter into separate, additional contractual arrangements for the non-commercial and non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this journal.
Authors are permitted and encouraged to post their published work online (e.g., in institutional repositories or on their website) as it can lead to productive exchanges, as well as earlier and greater citation of published work.
