Молодежный инновационный вестникМолодежный инновационный вестник2415-7805Федеральное государственное бюджетное образовательное учреждение высшего образования "Воронежский государственный медицинский университет имени Н.Н. Бурденко" Министерства здравоохранения Российской Федерации8813Conference ProceedingsMACHINE TRANSLATION OF MEDICAL TEXTSUzhovMatvei Aleksandrovichuzhov04@mail.ruhttps://orcid.org/0009-0006-3550-821XSapronovIlya Sergeevichsapron.i8800@gmail.comhttps://orcid.org/0009-0005-8426-9000Tver State Medical University290320231211741751504202316042023Copyright © 2023, uzhov M.A., Sapronov i.S.2023<p style="text-align: justify;">The article examines the feasibility of using machine translation of foreign texts containing medical terminology, based on the scientific accuracy of the translation of individual medical terms. The topic is of research interest because of the increasing need to use foreign, particularly English-language sources in research work. Translation services such as Google Translate, DeepL, Yandex Translator have been used. The services were selected on the basis of the answers received from the questionnaire survey of the students of Tver State Medical University. The authors randomly selected 50 English-language terms as translation material. The results obtained with each individual service were compared with the commonly used Russian-language counterpart, on the basis of which the clarity of the translation for the researcher's understanding was determined. The obtained data was summarised in a table, with the number of accurate and inaccurate translations expressed as a percentage for each individual service. The highest translation accuracy was observed for Google Translate (65%), the lowest for Yandex Translator (45%). The average number of matches is 53.3%. The authors conclude that machine translation currently does not provide the necessary accuracy when dealing with foreign text.</p>terminologymachine translationmedical texttranslation servicestranslatorsтерминологиямашинный переводмедицинский текстсервисы для переводапереводчики1.Müller M., Rios A., Sennrich R. Domain robustness in neural machine translation //arXiv preprint arXiv:1911.03109. – 2019. – DOI: 10.48550/arXiv.1911.03109.2.Vieira L. N., O’Hagan M., O’Sullivan C. Understanding the societal impacts of machine translation: a critical review of the literature on medical and legal use cases /Information, Communication & Society. – 2021. – Т. 24. – №. 11. – С. 1515–1532. – DOI: 10.1080/1369118X.2020.1776370