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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">sredob</journal-id><journal-title-group><journal-title xml:lang="ru">Здоровье населения и среда обитания – ЗНиСО</journal-title><trans-title-group xml:lang="en"><trans-title>Public Health and Life Environment – PH&amp;LE</trans-title></trans-title-group></journal-title-group><issn pub-type="ppub">2219-5238</issn><issn pub-type="epub">2619-0788</issn><publisher><publisher-name>ФБУЗ ФЦГиЭ Роспотребнадзора</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.35627/2219-5238/2021-29-7-82-85</article-id><article-id custom-type="elpub" pub-id-type="custom">sredob-601</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>ОБМЕН ОПЫТОМ</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="en"><subject>EXPERIENCE EXCHANGE</subject></subj-group></article-categories><title-group><article-title>Опыт использования нейронных сетей для прогнозирования исходов ишемического инсульта. Обзор литературы</article-title><trans-title-group xml:lang="en"><trans-title>Experience in Using Neural Networks to Predict the Outcomes of Ischemic Stroke: A Literature Review</trans-title></trans-title-group></title-group><contrib-group><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0003-4980-7617</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Дворжак</surname><given-names>В. С.</given-names></name><name name-style="western" xml:lang="en"><surname>Dvorzhak</surname><given-names>V. S.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Дворжак Владимир Сергеевич – аспирант кафедры общей гигиены</p><p>ул. Бутлерова, д. 49, г. Казань, 420012</p></bio><bio xml:lang="en"><p>Vladimir S. Dvorzhak, postgraduate student, Department of General Hygiene</p><p>49 Butlerov Street, Kazan, 420012</p></bio><email xlink:type="simple">dvorzhak1604@gmail.com</email><xref ref-type="aff" rid="aff-1"/></contrib><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0002-2073-2538</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Шулаев</surname><given-names>А. В.</given-names></name><name name-style="western" xml:lang="en"><surname>Shulaev</surname><given-names>A. V.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Шулаев Алексей Владимирович – доктор медицинских наук, заведующий кафедрой общей гигиены</p><p>ул. Бутлерова, д. 49, г. Казань, 420012</p></bio><bio xml:lang="en"><p>Alexey V. Shulaev, Dr. Sci. (Med.), Professor, Head of the Department of General Hygiene</p><p>49 Butlerov Street, Kazan, 420012</p></bio><email xlink:type="simple">shulaev8@gmail.com</email><xref ref-type="aff" rid="aff-1"/></contrib><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0002-8654-0408</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Вансовская</surname><given-names>Е. А.</given-names></name><name name-style="western" xml:lang="en"><surname>Vansovskaya</surname><given-names>E. A.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Вансовская Евгения Андреевна – студент V курса медико-биологического факультета</p><p>ул. Бутлерова, д. 49, г. Казань, 420012</p></bio><bio xml:lang="en"><p>Evgeniya A. Vansovskaya, a 5th year student, Faculty of Medical Biology</p><p>49 Butlerov Street, Kazan, 420012</p></bio><email xlink:type="simple">j.vansovskaya@gmail.com</email><xref ref-type="aff" rid="aff-1"/></contrib></contrib-group><aff-alternatives id="aff-1"><aff xml:lang="ru"><institution>ФГБОУ ВО «Казанский государственный медицинский университет» Минздрава России</institution><country>Россия</country></aff><aff xml:lang="en"><institution>Kazan State Medical University</institution><country>Russian Federation</country></aff></aff-alternatives><pub-date pub-type="collection"><year>2021</year></pub-date><pub-date pub-type="epub"><day>31</day><month>07</month><year>2021</year></pub-date><volume>0</volume><issue>7</issue><fpage>82</fpage><lpage>85</lpage><permissions><copyright-statement>Copyright &amp;#x00A9; Дворжак В.С., Шулаев А.В., Вансовская Е.А., 2021</copyright-statement><copyright-year>2021</copyright-year><copyright-holder xml:lang="ru">Дворжак В.С., Шулаев А.В., Вансовская Е.А.</copyright-holder><copyright-holder xml:lang="en">Dvorzhak V.S., Shulaev A.V., Vansovskaya E.A.</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://zniso.fcgie.ru/jour/article/view/601">https://zniso.fcgie.ru/jour/article/view/601</self-uri><abstract><p>Введение. Ишемический инсульт является структурно сложным заболеванием, в основе которого лежат разные патогенетические механизмы. Учитывая многокомпонентность данной патологии, а также ее сложную структуру, медицинским сообществом были созданы различные оценочные шкалы, в основе которых лежит оценка разных признаков. Данные шкалы созданы для того, чтобы прогнозировать возможное состояние пациента на различных этапах оказания медицинской помощи.Цель исследования. Определение актуальности использования системы прогнозирования исходов ишемического инсульта на базе нейронных сетей для совершенствования организации лечебного процесса пациентам, перенесшим ишемических инсульт.Материалы и методы. Был проведен анализ научной и медицинской литературы, посвященной вопросам создания и использования прогностических систем на базе искусственных нейронных сетей для прогнозирования исходов ишемического инсульта, а также самых распространенных оценочных шкал, которые в данное время используются в лечебной практике.Результаты. После проведенного анализа эффективности имеющихся шкал, был выявлен их главный недостаток – субъективная составляющая при оценке состояния того или иного пациента. В свою очередь, использование нейронных сетей позволяет минимизировать субъективную составляющую при формировании прогноза исхода ишемического инсульта. Данные результаты достигаются за счет того, что нейронные сети способны обрабатывать большие массивы данных, в результате чего устанавливаются скрытые взаимосвязи между объектами исследований.Выводы. Проведенный анализ отечественных и зарубежных источников доказывает, что наличие системы прогнозирования на базе нейронной сети является серьезным преимуществом для медицинской организации. Однако нейронные сети не в полной мере проходили клиническиe испытания, которые подтверждали бы превосходство нейронных сетей над современными методами прогнозирования исходов заболеваний, что является затруднением для их полноценного использования в клинической практике.</p></abstract><trans-abstract xml:lang="en"><p>Introduction. Ischemic stroke is a structurally complex disease based on various pathogenetic mechanisms. In view of the complexity of this pathology and its structure, the medical community has established various assessment scales based on different signs. The scales were created in order to predict possible conditions of a patient at various stages of treatment.The objective of our research was to determine the relevance of applying the system of predicting outcomes of ischemic stroke based on neural networks to improve ischemic stroke treatment and management.Materials and methods: We reviewed scientific and medical literature devoted to the development and use of forecasting systems based on artificial neural networks to predict outcomes of ischemic stroke and analyzed the most common assessment scales currently used in therapeutic practices.Results. The analysis of effectiveness of available scales revealed that their main drawback was a subjective component in the assessment of a patient’s condition. The use of neural networks, in its turn, minimizes the subjective component in predicting the outcome of ischemic stroke since neural networks are capable of processing large amounts of data and can, therefore, establish implicit correlation between research objects.Conclusion. The analysis of domestic and foreign literary sources proves that the presence of a forecasting system based on a neural network is a major advantage for a health care facility. Yet, neural networks have not fully passed clinical trials that would confirm their superiority over current methods of predicting disease outcomes, which impedes their extensive use in clinical practice.</p></trans-abstract><kwd-group xml:lang="ru"><kwd>здравоохранение</kwd><kwd>статистические данные</kwd><kwd>прогностические системы</kwd><kwd>нейронные сети</kwd><kwd>ишемический инсульт</kwd><kwd>общественное здоровье</kwd></kwd-group><kwd-group xml:lang="en"><kwd>health care</kwd><kwd>statistics</kwd><kwd>predictive systems</kwd><kwd>neural networks</kwd><kwd>ischemic stroke</kwd><kwd>public health</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">Скворцова В.И. Медицинская и социальная значимость проблемы инсульта // Качество жизни. 2004. № 4. С. 10–12.</mixed-citation><mixed-citation xml:lang="en">Skvortsova VI. 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