Treatment of tuberculosis currently requires the consideration of many factors. Timeliness of initiation, comprehensive treatment, and its correction during long-term chemotherapy are fundamental in achieving a positive result in a patient’s recovery. The purpose of the work is to create a doctor’s assistant in the form of an intelligent service for managing the treatment process in order to improve the quality of treatment. To achieve this goal, a platform for implementing intelligent services with knowledge bases has been created. The incorporated data was formed on the basis of ontology, which defines the terminology, the structure of the formed knowledge, as well as the rules of their generation and ontological conventions. Results. The basic tools of the platform include an ontology editor, as well as a knowledge base editor generator that automatically generates a knowledge editor with several types of user interfaces. The semantic representation and the knowledge editor, managed by ontology, provide an opportunity for the formation and maintenance of data by domain experts. The intelligent service is implemented as a system with an ontological knowledge base that has a semantic representation, which, along with the knowledge base editor, provides an opportunity to form and maintain the knowledge base for domain experts without intermediaries. The ontology knowledge and the generated knowledge base have a semantic representation that is understandable to users. Currently, the service is available and ready for practical use.
References
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21. Gribova V, Kleschev A, Moskalenko P, Timchenko V, Fedorischev L, Shalfeeva E. The IACPaaS Cloud Platform: Features and Perspectives // 2017 Second Russia and Pacific Conference on Computer Technology and Applications (RPC) (Vladivostok, Russia, 25-29 sept. 2017). IEEE. 2017. P. 80-84. doi : 10.1109/RPC.2017.8168076.
22. Gribova VV, Moskalenko PhM , Shalfeeva EA, Timchenko VA. Ontological Approach to Viable Decision Support Services Development. Advances in Intelligent Systems Research. 2020; 483: 274-277. doi : 10.2991/aisr.k.201029.052.
23. Cutsem van G, Isaakidis P, Farley J, Nardell E, Volchenkov G, Cox H. Infection control for drug-resistant tuberculosis: early diagnosis and treatment is the key. Clinical Infectious Diseases. 2016; 62(3): S238–S243.
2. Burmistrova I.A., Vaniev Je.V., Samojlova A.G., Lovacheva O.V., Vasil’eva I.A. Narastanie spektra lekarstvennoj ustojchivosti vozbuditelja na fone neadekvatnoj himioterapii tuberkuleza legkih. Tuberkulez i bolezni legkih. 2019; 97(8): 46-51. (In Russ).
3. Burakova M.V., Vasil’eva I.A., Vaniev Je.V., Bagdasarjan T.R., Samojlova A.G. Jeffektivnost ’ himioterapii tuberkuleza legkih u vpervye vyjavlennyh pacientov pri raznyh srokah opredelenija mnozhestvennoj lekarstvennoj ustojchivosti vozbuditelja. Tuberkulez i bolezni legkih. 2017; 95(11): 63-68. (In Russ).
4. Vasil’eva I.A., Belilovskij E.M., Borisov S.E., Sterlikov S.A. Tuberkulez s mnozhestvennoj lekarstvennoj ustojchivost’ju vozbuditelja v stranah mira i v rossijskoj federacii. Tuberkulez i bolezni legkih. 2017; 95(11): 5-18. (In Russ).
5. Gribova V.V. et al. Oblachnaja platforma IACPaaS dlja razrabotki obolochek intellektual’nyh servisov : sostojanie i perspektivy razvitija. Programmnye produkty i sistemy. 2018; 31(3). (In Russ).
6. Gribova V.V., Kovalev R.I., Okun’ D.B. Specializirovannaja obolochka dlja postroenija intellektual’nyh sistem naznachenija medikamentoznogo lechenija. Iskusstvennyj intellekt i prinjatie reshenij. 2020; 4: 66-79. (In Russ).
7. Gribova V.V., Kleshhev A.S., Moskalenko F.M., Timchenko V.A., Shalfeeva E.A. Rasshirjaemyj instrumentarij dlja sozdanija zhiznesposobnyh sistem s bazami znanij. Programmnaja inzhenerija. 2018; 9(8): 339-348. (In Russ). doi : 10.17587/prin.9.339-348.
8. Gribova V.V., Fedorishhev L.A. Oblachnyj servis dlja formirovanie formalizovannyh istorij bolezni. Vrach i informacionnye tehnologii. 2020; 1: 51-57. (In Russ).
9. Gribova V.V., Shalfeeva E.A. Sistemy na osnove ontologicheskih baz znanij kak osnova dlja sozdanija sovremennyh sistem iskusstvennogo intellekta. Trudy konferencii « Vosemnadcataja Nacional’naja konferencija po iskusstvennomu intellektu s mezhdunarodnym uchastiem KII-2020»; Moskva, 10-16 okt 2020. M.: MFTI, 2020: 12-19. (In Russ).
10. Moskalenko F.M., Okun’ D.B., Petrjaeva M.V. Baza terminov dlja intellektual’nyh medicinskih servisov. Materialy X mezhdunarodnoj nauchnoj konferencii « Sistemnyj analiz v medicine» (SAM 2016). Blagoveshhensk , 2016: 155-158. (In Russ).
11. Gajda A.I., Sveshnikova O.M., Verhovaja V.N., Mahmaeva S.V., Nikishova E.I., Mar’jandyshev A.O. Lechenie bol’nyh s shirokoj lekarstvennoj ustojchivost’ju mikobakterij s primeneniem novyh protivotuberkuleznyh preparatov v grazhdanskom obshhestve Arhangel’skoj oblasti. Tuberkulez i bolezni legkih. 2018; 96(7): 5-10. (In Russ).
12. Nechaeva O.B. Jepidemiologicheskaja situacija po tuberkulezu v Rossii. Tuberkulez i bolezni legkih. 2018; 96(8): 15-24. (In Russ).
13. Sterlikov S.A., Rusakova L.I. Model’ jepidemicheskoj situacii po tuberkulezu s shirokoj lekarstvennoj ustojchivost’ju v regionah Rossii. Vestnik central’nogo nauchno-issledovatel’skogo instituta tuberkul eza. 2018; 2: 66-73. (In Russ).
14. Miller AC, Keshavjee S, Atwood S, Ahmad Khan F, Livchits V, Vasilyeva I, Kornienko S, Kononenko Y. Turning off the tap: using the fast approach to stop the spread of drug-resistant tuberculosis in the Russian Federation. Journal of Infectious Diseases. 2018; 218(4): 654-658.
15. Reuter A, Furin J. Reducing harm in the treatment of multidrug-resistant tuberculosis. [Electronic resourse ]. Available at: https://www.sciencedirect.com/science/article/pii/S2405579419300361. Last accessed on : Apr 04 , 2021.
16. Gribova VV, Kleshchev AS, Moskalenko FM, Timchenko VA. A Model for Generation of Directed Graphs of Information by the Directed Graph of Metainformation for a Two_Level Model of Information Units with a Complex Structure. Automatic Documentation and Mathema tical Linguistics. 2015; 49(6): 221-231.
17. Udwadia Z, Furin J. Quality of drug-resistant tuberculosis care: gaps and solutions. [Electronic resourse ]. Available at: https://pubmed.ncbi.nlm.nih.gov/31720427. Last accessed on : Apr 04 , 2021.
18. Mayanja- Kizza H, Sekaggya -Wiltshire C, Kassa D. Optimal therapy for multidrug-resistant tuberculosis and HIV. Lancet. 2020; 396: 363-365.
19. World Health Organization. Global Tuberculosis Report 2020 [Electronic resourse ]. Available at: https://apps.who.int/iris/bitstream/handle/10665/336069/ 9789240013131. Last accessed on : Apr 0 2, 2021.
20. Seung KJ, Keshavjee S, Rich ML. Multidrug-Resistant Tuberculosis and Extensively Drug-Resistant Tuberculosis. [Electronic resourse ]. Available at: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4561400. Last accessed on : Apr 04 , 2021.
21. Gribova V, Kleschev A, Moskalenko P, Timchenko V, Fedorischev L, Shalfeeva E. The IACPaaS Cloud Platform: Features and Perspectives // 2017 Second Russia and Pacific Conference on Computer Technology and Applications (RPC) (Vladivostok, Russia, 25-29 sept. 2017). IEEE. 2017. P. 80-84. doi : 10.1109/RPC.2017.8168076.
22. Gribova VV, Moskalenko PhM , Shalfeeva EA, Timchenko VA. Ontological Approach to Viable Decision Support Services Development. Advances in Intelligent Systems Research. 2020; 483: 274-277. doi : 10.2991/aisr.k.201029.052.
23. Cutsem van G, Isaakidis P, Farley J, Nardell E, Volchenkov G, Cox H. Infection control for drug-resistant tuberculosis: early diagnosis and treatment is the key. Clinical Infectious Diseases. 2016; 62(3): S238–S243.
For citation
Borodulina Е. А., Gribova V.V., Eremenko E.P., Borodulin E.B., Kolsanov A.V., Okun D.B., Uraksina M.V., Kovalev R.I., Fedorishchev L.A. Intelligent service for managing the treatment of patients with pulmonary tuberculosis. Medical doctor and information technology. 2021; 2: 36-45. (In Russ.). doi : 1025881/18110193_2021_2_36.
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