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<article article-type="research-article" dtd-version="1.3" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xml:lang="ru"><front><journal-meta><journal-id journal-id-type="publisher-id">natszdrav</journal-id><journal-title-group><journal-title xml:lang="ru">Национальное здравоохранение</journal-title><trans-title-group xml:lang="en"><trans-title>National Health Care (Russia)</trans-title></trans-title-group></journal-title-group><issn pub-type="ppub">2713-069X</issn><issn pub-type="epub">2713-0703</issn><publisher><publisher-name>Federal State Autonomous Educational Institution of Higher Education I.M. Sechenov First Moscow State Medical University of the Ministry of Health of the Russian Federation (Sechenov University)</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.47093/2713-069X.2023.4.4.48-55</article-id><article-id custom-type="elpub" pub-id-type="custom">natszdrav-315</article-id><article-categories><subj-group subj-group-type="heading"><subject>Research Article</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="ru"><subject>ИНФОРМАТИЗАЦИЯ ЗДРАВООХРАНЕНИЯ</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="en"><subject>INFORMATIZATION OF HEALTHCARE</subject></subj-group></article-categories><title-group><article-title>Перспективы применения больших языковых моделей в здравоохранении</article-title><trans-title-group xml:lang="en"><trans-title>Perspectives on the application of large language models in healthcare</trans-title></trans-title-group></title-group><contrib-group><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0001-6359-0763</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Андрейченко</surname><given-names>А. Е.</given-names></name><name name-style="western" xml:lang="en"><surname>Andreychenko</surname><given-names>A. E.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Андрейченко Анна Евгеньевна – канд. физ.-мат. наук, руководитель направления искусственного интеллекта</p><p>набережная Варкауса, д. 17, г. Петрозаводск, 185031</p></bio><bio xml:lang="en"><p>Anna E. Andreychenko – Cand. of Sci. (Physics and Mathematics), Head of Artificial Intelligence</p><p>Varkaus Embankment, 17, Petrozavodsk, 185031</p></bio><xref ref-type="aff" rid="aff-1"/></contrib><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0002-7380-8460</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Гусев</surname><given-names>А. В.</given-names></name><name name-style="western" xml:lang="en"><surname>Gusev</surname><given-names>A. V.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Гусев Александр Владимирович – канд. техн. наук, старший научный сотрудник отдела научных основ организации здравоохранения, старший научный сотрудник</p><p>ул. Добролюбова, д. 11, г. Москва, 127254</p><p>ул. Петровка, д. 24, г. Москва, 127051</p></bio><bio xml:lang="en"><p>Aleksandr V. Gusev – Cand. of Sci. (Technology), Senior Researcher, Department of Scientific Foundations of Healthcare Organization, Senior Researcher</p><p>Dobrolyubova str., 11, Moscow, 127254</p><p>Petrovka str., 24/1, Moscow, 127051</p></bio><email xlink:type="simple">agusev@webiomed.ai</email><xref ref-type="aff" rid="aff-2"/></contrib></contrib-group><aff-alternatives id="aff-1"><aff xml:lang="ru"><institution>ООО «К-Скай»</institution><country>Россия</country></aff><aff xml:lang="en"><institution>K-Skai LLC</institution><country>Russian Federation</country></aff></aff-alternatives><aff-alternatives id="aff-2"><aff xml:lang="ru"><institution>ФГБУ «Центральный научно-исследовательский институт организации и информатизации здравоохранения» Министерства здравоохранения Российской Федерации; ГБУЗ г. Москвы «Научно-практический клинический центр диагностики и телемедицинских технологий Департамента здравоохранения Москвы»</institution><country>Россия</country></aff><aff xml:lang="en"><institution>Federal Research Institute for Health Organization and Informatics; Research and Practical Clinical Center for Diagnostics and Telemedicine Technologies</institution><country>Russian Federation</country></aff></aff-alternatives><pub-date pub-type="collection"><year>2023</year></pub-date><pub-date pub-type="epub"><day>03</day><month>04</month><year>2024</year></pub-date><volume>4</volume><issue>4</issue><fpage>48</fpage><lpage>55</lpage><permissions><copyright-statement>Copyright &amp;#x00A9; Андрейченко А.Е., Гусев А.В., 2024</copyright-statement><copyright-year>2024</copyright-year><copyright-holder xml:lang="ru">Андрейченко А.Е., Гусев А.В.</copyright-holder><copyright-holder xml:lang="en">Andreychenko A.E., Gusev A.V.</copyright-holder><license xml:lang="ru" license-type="creative-commons-attribution" xlink:href="https://creativecommons.org/licenses/by/4.0/" xlink:type="simple"><license-p>Данная работа распространяется под лицензией Creative Commons Attribution 4.0.</license-p></license><license xml:lang="en" license-type="creative-commons-attribution" xlink:href="https://creativecommons.org/licenses/by/4.0/" xlink:type="simple"><license-p>This work is licensed under a Creative Commons Attribution 4.0 License.</license-p></license></permissions><self-uri xlink:href="https://www.natszdrav.ru/jour/article/view/315">https://www.natszdrav.ru/jour/article/view/315</self-uri><abstract><p>Большие языковые модели стали новым значимым прорывом в области искусственного интеллекта, меняющим подходы от применения моделей машинного обучения в узких задачах, требующих больших объемов данных с готовыми ответами для обучения, к генеративным моделям, способным к дообучению на небольшом количестве примеров или вообще без примеров с готовыми ответами и при этом имеющих более широкие возможности применения. Медицина является одной из областей, в которой внедрение больших языковых моделей может стать крайне востребованным. В обзоре представлены данные о последних достижениях применения больших языковых моделей для медицинских задач, перспективы использования этих моделей как основы цифровых ассистентов для врачей и пациентов, а также существующие регуляторные и этические барьеры на пути развития этой прорывной технологии для решения задач здравоохранения.</p></abstract><trans-abstract xml:lang="en"><p>Large language models have become a new significant breakthrough in the field of artificial intelligence. They are changing approaches to machine learning from models that solve narrow problems and require large amounts of data with the known answers for training, to generative models that are fine tunable to solve specific problems using a small number of examples with the known answers or even none at all. Medicine is one of the areas in which the use of large language models can become extremely useful. The review presents data on the latest achievements in the use of large language models for medical tasks, prospects for using these models as the basis for the digital assistants for doctors and patients, as well as existing regulatory and ethical barriers to the development of this breakthrough technology for addressing healthcare challenges.</p></trans-abstract><kwd-group xml:lang="ru"><kwd>большие языковые модели</kwd><kwd>генеративный искусственный интеллект</kwd><kwd>здравоохранение</kwd><kwd>машинное обучение</kwd><kwd>медицинский чат-бот</kwd></kwd-group><kwd-group xml:lang="en"><kwd>large language models</kwd><kwd>generative artificial intelligence</kwd><kwd>healthcare</kwd><kwd>machine learning</kwd><kwd>medical chatbot</kwd></kwd-group></article-meta></front><back><ref-list><title>References</title><ref id="cit1"><label>1</label><citation-alternatives><mixed-citation xml:lang="ru">Yang R., Tan T.F., Lu W., et al. 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