Preview

Yakut Medical Journal

Advanced search

Cloud service for the differential clinical diagnostics of acute respiratory viral diseases (including those associated with highly contagious coronaviruses) with an application of methods of artificial intelligen

https://doi.org/10.25789/YMJ.2020.70.13

Abstract

This paper presents the results of the development of a medical diagnostic service that is based on a model of medical knowledge and an intelligent decision-maker. The development of decision support systems that accumulate advanced knowledge in the diagnosis and treatment of diseases is an important area of medical informatization. Such systems are especially relevant in the period of major epidemic outbreaks, when a huge number of doctors of various profiles are involved in the process of diagnosis, time for decision-making and prescription of treatment is very short, and the diagnosis itself, due to continuous acquisition of new knowledge, is constantly being improved and refined. The methods of artificial intelligence with ontological knowledge bases are the most ready for this challenge. The work describes a cloud service implemented on the IACPaaS platform for differential diagnosis of coronavirus infections (SARS, MERS and COVID-19) from other infections of the respiratory tract of viral etiology.

About the Authors

V. V. Gribova
Institute of Automation and Control Processes of the Far Eastern Branch of the Russian Academy of Sciences; School of Natural Sciences of the Far Eastern Federal University
Russian Federation

Valeria V. Gribova – Doctor of Technical Sciences, Deputy Director for Research and a Head of the Laboratory of Intelligent Systems;

Professor

tel.: +79084498959

Vladivostok



B. O. Dmitry
Institute of Automation and Control Processes of the Far Eastern Branch of the Russian Academy of Sciences
Russian Federation

Dmitry B. Okun – Ph.D., Researcher at the Laboratory of Intelligent Systems

tel.: +74232310424

Vladivostok



E. A. Shalfeeva
Institute of Automation and Control Processes of the Far Eastern Branch of the Russian Academy of Sciences
Russian Federation

Elena A. Shalfeeva – Ph.D., Senior Researcher at the Laboratory of Intelligent Systems

tel.: +74232674170

Vladivostok



B. O. Shcheglov
School of Biomedicine of the far Eastern Federal University
Russian Federation

Bogdan O. Shcheglov – Student

Vladivostok

tel.: +79147189825



M. Yu. Shchelkanov
Far East Federal University; Far Eastern Branch of the Russian Academy of Sciences
Russian Federation

Mikhail Yu. Shchelkanov – Doctor of Biology, Head of the International Scientific and Educational Center of Biological Safety;

Head of Laboratory of Virology, Federal Scientific Center of East Asia Terrestrial Biodiversity

Senior Researcher at the Laboratory of Marine Mammals

National Scientific Center of Marine Biology, Far Eastern Branch of the Russian Academy of Sciences, (Vladivostok);

Vladivostok

tel.: +79032689098



References

1. Gribova V.V. Knowledge base ontology for disease treatment / V.V. Gribova, D.B. Okun, D.A. Krasnov // System analysis in medicine (SAM 2017). Materials of the XI international scientific conference. – Blagoveshchensk: Amur Medical Academy, 2017. – P. 60–63.

2. Gribova V.V. Medical Diagnosis Ontology For Intelligent Decision Support Systems / V.V. Gribova, M.V. Petryaeva, D.B. Okun, E.A. Shalfeeva // Ontology of Designing. – 2018. – 8(1). – P 58-73. DOI: 10.18287/2223-9537-2018-8-1-58-73.

3. Methods and tools of viable intelligent services development / V.V. Gribova, A.S. Kleschev, F.M. Moskalenko [et al.] // Vestnik of Far Eastern Branch of Russian Academy of Sciences. – 2016. – № 4. – P. 133–141.

4. Ministry of Public Health of the Russian Federation. Prevention, diagnosis and treatment of novel coronavirus infection (2019-nCoV). Temporary guidelines (version from 03.02.2020). – M., 2020. – 52 p.

5. IACPaaS cloud platform for the development of intelligent service shells: current state and future evolution / V.V. Gribova, A.S. Kleschev, Ph.M. Moskalenko [et al.] // Software & Systems. – 2018. – № 3. – P. 527–536. DOI: 10.15827/0236-235X.031.3.527-536.

6. Pandemic influenza in Russia: specific features of clinical course and the absence of early etiotropic therapy as a risk factor of severe forms of the disease / L.V. Kolobukhina, L.N. Merkulova, M.Yu. Schelkanov [et al.] // Ter. Arkh. – 2011. – V. 83, № 9. – P. 48–53.

7. Application of modern molecular-biological techniques for provision of biological safety / D.K. Lvov, S.V. Alkhovsky, M.Yu. Schelkanov [et al.] // Vestnik Rossiiskoi voenno-medicinskoi academii. – 2014. – № 3. – P. 115–127.

8. Pulmonology. National guidance / Ed. A.G. Chuchalin. – M.: GEOTAR-Media, 2016. – 800 p.

9. Handbook of Virology. Viruses and viral infections of humans and animals / Ed. D.K. Lvov. – M.: Med. Inf. Agency, 2013. – 1200 p.

10. Chuchalin A.G. Severe acute respiratory syndrome / A.G. Chuchalin // Ter. Arch. – 2004. – V. 76. – № 3. – P. 5–11.

11. Shchelkanov M.Yu. Middle East respiratory syndrome: when will smoldering focus outbreak ? / M.Yu. Shchelkanov, V.Yu. Ananiev, V.V. Kuznetsov, V.B. Shumatov // Pacific Medical Journal. – 2015. – № 2. – P. 94–98.

12. Shchelkanov M.Yu. Influenza: history, clinics, pathogenesis / M.Yu. Shchelkanov, L.V. Kolobukhina, D.K. Lvov // The Practitioner. – 2011. – № 10. – P. 33–38. URL: https://www.lvrach.ru/2011/10/15435275/

13. Shchelkanov M.Yu. Human coronaviruses (Nidovirales, Coronaviridae): increased level of epidemic threat / M.Yu. Shchelkanov, L.V. Kolobukhina, D.K. Lvov // The Practitioner. – 2013. – № 10. – P. 49–54. URL: http://www.lvrach.ru/2013/10/15435832/

14. Shchelkanov M.Yu. Epidemic outbreak of Middle East respiratory syndrome in the Republic of Korea (May-July, 20015): reasons, dynamics, conclusions / M.Yu. Shchelkanov, V.Yu. Ananiev, V.V. Kuznetsov, V.B. Shumatov // Pacific Medical Journal. – 2015. – V. 3. – P. 25–29.

15. Chinese National Committee on Public Health and Traditional Chinese Medicine. Program for the diagnosis and treatment of pneumonia associated with a new coronavirus infection. 4-th edition. – Bejing, 2020. – 74 p. (In Chinese)

16. Genomic characterization and epidemiology of 2019 novel coronavirus: implications for virus origins and receptor binding / R. Lu, X. Zhao, J. Li [et al.] // The Lancet. – 2020. 395(10224). P. 565-574. DOI: 10.1016/S0140-6736(20)30251-8.

17. Liu P. Viral Metagenomics Revealed Sendai Virus and Coronavirus Infection of Malayan Pangolins (Manis javanica) / P. Liu, W. Chen, J.P. Chen // Viruses. 2019. – V. 11. – № 11. – P. E979. DOI: 10.3390/v11110979.

18. World Health Organization. Coronavirus disease 2019 (COVID-19). Situation Report-40 (29 February 2020). URL: https://www.who.int/docs/default-source/coronaviruse/situation-reports/20200229-sitrep-40-covid-19.pdf?sfvrsn=849d0665_2 (accessed 06.03.2020).


Review

For citations:


Gribova V.V., Dmitry B.O., Shalfeeva E.A., Shcheglov B.O., Shchelkanov M.Yu. Cloud service for the differential clinical diagnostics of acute respiratory viral diseases (including those associated with highly contagious coronaviruses) with an application of methods of artificial intelligen. Yakut Medical Journal. 2020;(2):44-47. https://doi.org/10.25789/YMJ.2020.70.13

Views: 14


Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.


ISSN 1813-1905 (Print)
ISSN 2312-1017 (Online)