Perm Medical JournalPerm Medical Journal0136-14492687-1408Eco-Vector337110.17816/pmj32463-67Research ArticleNEURONET SYSTEM FOR INFANTILE ALLERGIC AND INFECTIOUS RHINITIS DIAGNOSISMinaevaN Vdocnvm@mail.ruKumpanN A-YasnitskyL N-ShiryaevaD M-15082015324636712072016Copyright © 2015, Minaeva N.V., Kumpan N.A., Yasnitsky L.N., Shiryaeva D.M.2015Aim. To develop the system of differential diagnosis of infectious and allergic rhinitis. Materials and methods. The data of 217 children with infectious and allergic rhinitis were used to develop the diagnostic system based on neuron network technology. Results. Differential diagnostic system permitting to diagnose with great accuracy “infectious rhinitis” and “allergic rhinitis” by means of minimum number of input parameters was worked out. Virtual computer experiments, estimating the role of passive smoking for the purpose of predicting these diseases, indicated contradictory results requiring further studies. Conclusions. The diagnostic system worked out can be used by the principle of “preliminary diagnosis of allergic rhinitis without allergologist” in the work of pediatricians, therapeutists, general practitioners as well as for screening diagnosis in conditions of “Health Centers”.Allergic rhinitisinfectious rhinitisdiagnosisneuron networksmokingmathematical modelРинит аллергическийринит инфекционныйдиагнознейронная сетькурениематематическая модель[Черепанов Ф. М., Ясницкий Л. Н. Нейросимулятор 5.0. Свидетельство о государственной регистрации программы для ЭВМ № 2014618208. Заявка Роспатент № 2014614649. Зарегистрировано в Реестре программ для ЭВМ 12.08.2014.][Ясницкий Л. Н., Думлер А. А., Богданов К. В., Полещук А. Н., Черепанов Ф. М., Макурина Т. В., Чугайнов С. В. Диагностика и прогнозирование течения заболеваний сердечно-сосудистой системы на основе нейронных сетей. Медицинская техника 2013; 3: 42-44.][Ясницкий Л. Н. Нейронные сети - инструмент для получения новых знаний: успехи, проблемы, перспективы. Нейрокомпьютеры: разработка, применение 2015; 5: 48-56.][Das R., Turkoglu I., Sengur A. Effective diagnosis of heart disease through neural networks ensembles. Expert Systems with Applications 2009; 36(4): 7675-7680.][Johnsson D., Gil M., Garicia Chemizo J. M., Paya A. S., Fernandez D. R. Application of artificial neural networks in the diagnosis of urological dysfunctions. Expert Systems with Applications 2009; 36 (3): 5754-5760.][Yumusak O. E. N., Temurtas F. Chest diseases diagnosis using artificial neural networks. Expert Systems with Applications 2010; 37 (12): 7648-7655.][Yasnitsky L. N., Dumler A. A., Poleshchuk A. N., Bogdanov C. V., Cherepanov F. M. Artificial neural networks for obtaining new medical knowledge: diagnostics and prediction of cardiovascular disease progression. Biol. Med. (Aligarh) 2015; 7(2): BM-095-15,8.]