S.V. Frolov1, D.E. Sudakov2, A.A. Korobov3, D.G. Styrykh4

1–4 Tambov State Technical University (Tambov, Russia)
1 sergej.frolov@gmail.com, 2 sudakov.dima1702@yandex.ru, 3 korobov1991@mail.ru, 4 staryh.danya@yandex.ru

Problem statement. The problem under consideration is caused by the need to develop an effective system for monitoring the condition of pediatric patients with a diagnosed ventricular septal defect. Within the framework of the proposed approach, special attention is paid to the creation of a model that allows predicting the development of potentially dangerous hemodynamic disorders.

Work purpose. development of a method for in silico modeling of the current functional status and dynamics of changes in the cardiovascular system in children with VSD, aimed at optimizing clinical decision-making and reducing the level of infant mortality.

Results. A specialized software package for mathematical modeling of the cardiovascular system in children with ventricular septal defect has been developed. The created system provides comprehensive forecasting of the physiological state of a developing organism, taking into account age-related hemodynamic characteristics. The developed computational system incorporates a comprehensive multiparametric model capable of quantitative risk stratification for impending critical cardiovascular events, early detection of preclinical hemodynamic disturbances, and in silico evaluation of therapeutic interventions. This integrated modeling framework enables probabilistic assessment of pathophysiological progression while providing clinically actionable insights through simulation-based treatment optimization.

Practical significance. of the study results lies in the possibility of preventing life-threatening complications through timely detection of negative trends in changes in hemodynamic parameters.

Frolov S.V., Sudakov D.E., Korobov A.A., Starykh D.G. System of support for medical decision-making for early diagnosis of children with ventricular septal defect. Biomedicine Radioengineering. 2026. V. 29. № 1. P. 18–23. DOI: https:// doi.org/10.18127/j15604136-202601-04 (In Russian)

1. Zhang X., Haneishi H., Liu H. Multiscale modeling of the cardiovascular system for infants, children, and adolescents: Age-related alterations in cardiovascular parameters and hemodynamics. Computers in Biology and medicine. 2019. № 108. P. 200–212.
2. GOST R 71671–2024. Sistemy podderzhki prinyatiya vrachebnyh reshenij (SPPVR) s ispol'zovaniem iskusstvennogo intellekta. Trebovaniya k funkcional'nosti i bezopasnosti. Vved. 2025-01-01. M.: Standartinform, 2024. 24 s. (In Russian).
3. Aleksandrovich A.S., Zimatkina T.I., Zukovskaya K.G., Shidlovskaya A.S. Possibilities of antenatal ultrasound diagnosis of congenital heart defects. Innovacionnye nauchnye issledovaniya. 2023. № 5–2(29). C. 19–25. URL: https://ip-journal.ru/.
4. Berner E.S., Tonya J.L. Clinical Decision Support Systems: Theory and Practice. 2. New York: Springer Science and Business Media. 2007. P. 3–22.
5. Frolov S.V., Sindeev S.V., Lischouk V.A. A lumped parameter model of cardiovascular system with pulsating heart for diagnostic studies. Journal of Mechanics in Medicine and Biology 2017. № 17(5). 1750056 (21).
6. Basarab M.A., Konnova N.S., Mitrohin V.N., Basarab D.A., Macievskij D.D. Diagnostika sostoyanij serdechno-sosudistoj sistemy metodami nelinejnoj cifrovoj obrabotki signalov doplerovskih izmeritelej skorosti krovotoka. Biomedicinskaya radioelektronika. 2017. № 5. S. 3–12 (In Russian).
7. Tsiklidis E.J., Sinno T., Diamond S.L. Coagulopathy implications using a multiscale model of traumatic bleeding matching macro- and microcirculation. The American Journal of Physiology-Heart and Circulatory Physiology. 2019. №317(1). P. 73–86.
8. Frolov S.V., Lyadov M.A., Ostapenko O.A. Ekspertnaya sistema ocenki fizicheskogo razvitiya rebenka na osnove apparata relyacionnoj algebry. Biotekhnosfera. 2013. №6(30). C. 28 (In Russian).
9. Frolov S.V. Sudakov D.E. Staryh D.G. Postroenie zavisimostej izmeneniya parametrov organizma rebenka ot vozrasta. Modelirovanie, optimizaciya i informacionnye tekhnologii. 2024;12(3). URL: https://moitvivt.ru/ru/journal/pdf?id=1622 DOI: 10.26102/2310-6018/2024.46.3.004 (In Russian).
10. Gavrilov D.V., Serova L.M., Korsakov I.N. i dr. Predskazanie serdechno-sosudistyh sobytij pri pomoshchi kompleksnoj ocenki faktorov riska s ispol'zovaniem metodov mashinnogo obucheniya. Vrach. Nauchno-prakticheskij zhurnal. 2020. № 5. S. 41–45 (In Russian).
11. Zhuleva S.Yu., Kroshilin A.V., Kroshilina S.V. Podderzhka prinyatiya upravlencheskih medicinskih reshenij i priroda neopredelennosti v nih. Biomedicinskaya radioelektronika. 2021. № 4. S. 89–96 (In Russian).