МЕТОДИКА ДИФФЕРЕНЦИАЛЬНОЙ ДИАГНОСТИКИ НОЗОЛОГИЧЕСКОЙ ФОРМЫ ВИРУСНОГО ГЕПАТИТА С ПРИМЕНЕНИЕМ НЕЙРОННОЙ СЕТИ КАСКАДНОЙ КОРРЕЛЯЦИИ
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Научный журнал Моделирование, оптимизация и информационные технологииThe scientific journal Modeling, Optimization and Information Technology
Online media
issn 2310-6018

METHOD OF DIFFERENTIAL DIAGNOSTICS OF THE NOSOLOGICAL FORM OF VIRAL HEPATITIS WITH THE APPLICATION OF NEURAL NETWORK OF CASCADE CORRELATION

Astafiev A.N. 

UDC 004.891.3
DOI: 10.26102/2310-6018/2019.26.3.028

  • Abstract
  • List of references
  • About authors

An important aspect of determining the nosological form of hepatitis is the combination of input data at the beginning of the study. The use of neural networks in medicine, which have the ability to search for hidden dependencies by learning from the experience of doctors, makes it easier to work in the role of advisor. However, the question of selecting the most effective topology for a specific task remains open. This paper substantiates the need to use neural network algorithms to solve the problem of determining the nosological form of hepatitis. The analysis and selection of input factors characterizing the clinical condition of the patient, and output factors characterizing the specific nosological form of hepatitis, neural network. The algorithm, its use is described, and a cascade neural network is compared with others in the context of the problem under consideration. At the end, a description is made of the established system for determining the nosological form of hepatitis using a cascade correlation neural network, and also describes the clinical efficacy

1. Lapasov S.H., Hakimova L.R., Ablakulova M.H., Valieva M.H. Diagnostika, lechenie i profilaktika hronicheskogo gepatita b s pozicii dokazatel'noj mediciny // Kurskij nauchno-prakticheskij vestnik «CHelovek i ego zdorov'e». 2015. №3. S. 41-48.

2. Baranov A. A., Kaganov B. S., Uchajkin V. F., Korsunskij A. A., Gorelov A. V., Potapov A. S., Balikin V. F., Il'in A. G., Konova S. R., Kotovich M. M., Lytkina I. N., Mihajlov M. I., Nikitin I. G., Nikolaeva L. I., Rejzis A. R., Sichinava I. V., Strokova T. V., Talalaev A. G., Tamazyan G. V., Tumanova E. L., CHerednichenko T. V., SHilyaev R. R., SHuvakova N. I., YAcenko E. A. Diagnostika i lechenie hronicheskih virusnyh gepatitov v, s i d u detej // Voprosy sovremennoj pediatrii. 2004. T.3. №6. S. 35-38.

3. Pimenov N.N., CHulanov V.P., Komarova S.V., Karandashova I.V., Neverov A.D., Mihajlovskaya G.V., Dolgin V.A., Lebedeva E.B., Pashkina K.V., Korshunova G.S., Gepatit s v Rossii: epidemiologicheskaya harakteristika i puti sovershenstvovaniya diagnostiki i nadzora // Epidemiologiya i infekcionnye bolezni. 2012. №3. S. 4-10.

4. Asadov D.A. Klinicheskoe rukovodstvo po diagnostike, lecheniyu i profilaktike hronicheskih gepatitov u vzroslyh v pervichnom zvene zdravoohraneniya. Tashkent, 2013. 47 s.

5. Fazylov V.H. Etiologicheskie i patogeneticheskie aspekty diagnostiki i lecheniya virusnyh gepatitov // Kazanskij medicinskij zhurnal. 2013. №6. S. 785-792.

6. Simmonds P., Bukh J., Combet C. et al. Consensus proposals for a unified system of nomenclature of hepatitis C virus genotypes // Hepatology. 2005. Vol. 42, N 4. P. 962–973.

7. Astaf'ev A.N., Kavygin V.V. Nejronnaya set' dlya ocenki effektivnosti lecheniya gepatita // Mediko-ekologicheskie informacionnye tekhnologii – 2016: XIX Mezhdunarodnaya nauchno-tekhnicheskaya konferenciya. Kursk: YUgo-zapadnyj tekhnicheskij universitet, 2016. S. 68–74.

8. Kryuchin O. V., Arzamascev A. A. Parallel'nyj algoritm samoorganizacii struktury iskusstvennoj nejronnoj seti // Vestnik Tambovskogo universiteta. Seriya: Estestvennye i tekhnicheskie nauki. 2011. №1. S. 199 – 200.

9. Kryuchin O. V., Arzamascev A. A. Sravnenie effektivnosti posledovatel'nyh i parallel'nyh algoritmov obucheniya iskusstvennyh nejronnyh setej na klasternyh vychislitel'nyh sistemah // Vestnik Tambovskogo universiteta. Seriya: Estestvennye i tekhnicheskie nauki. 2010. №6. S. 1872-1889.

10. Artyuhin V. V., Gorbachenko V. I., Solomaha A. A. Komp'yuternaya programma diagnostiki virusnogo gepatita // VNMT. 2007. №2. S. 141-142.

11. Kaczmarz S. Approximate solution of systems of linear equations. Internat. J. Control, 1993, vol. 57, no. 6, pp. 1269–1271.

12. Dmitriev G.A., Astaf'ev A.N. Sistema podderzhki prinyatiya reshenij pri opredelenii nozologicheskoj formy gepatita // Programmnye produkty i sistemy. 2017. №4. S. 754-757.

13. Gerashchenko S.I Ispol'zovanie nejrosetevogo klassifikatora dlya identifikacii novoobrazovanij /Gerashchenko S.I., Gerashchenko S.M., YAnkina N.N., Engalychev F.SH.//Nejrokomp'yutery: razrabotka, primenenie. 2008. № 9. S. 77-80.

14. Gerashchenko S.I. Vybor optimal'noj struktury nejroseti dlya fil'tracii signala v zadache dzhoul'metricheskogo metoda ocenki sostoyaniya biologicheskih ob"ektov /Gerashchenko S.I., Gerashchenko S.M., Martynov I.YU. //Izvestiya TRTU. 2006. № 11 (66). S. 68-69.

Astafiev Andrey Nikolaevich

Email: awastav47@yandex.ru

Lipetsk State Technical University

Lipetsk, Russian Federation

Keywords: neural network, viral hepatitis, nosological form of hepatitis, neural network of cascade correlation, classification

For citation: Astafiev A.N. METHOD OF DIFFERENTIAL DIAGNOSTICS OF THE NOSOLOGICAL FORM OF VIRAL HEPATITIS WITH THE APPLICATION OF NEURAL NETWORK OF CASCADE CORRELATION. Modeling, Optimization and Information Technology. 2019;7(3). URL: https://moit.vivt.ru/wp-content/uploads/2019/09/Astafev_3_19_1.pdf DOI: 10.26102/2310-6018/2019.26.3.028 (In Russ).

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Published 30.09.2019