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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">vitj</journal-id><journal-title-group><journal-title xml:lang="ru">Врач и информационные технологии</journal-title><trans-title-group xml:lang="en"><trans-title>Medical Doctor and Information Technologies</trans-title></trans-title-group></journal-title-group><issn pub-type="ppub">1811-0193</issn><issn pub-type="epub">2413-5208</issn><publisher><publisher-name>Pirogov National Medical and Surgical Center</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.25881/18110193_2026_1_38</article-id><article-id custom-type="elpub" pub-id-type="custom">vitj-311</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>ОБЗОРЫ</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="en"><subject>REVIEWS</subject></subj-group></article-categories><title-group><article-title>Влияние цифровизации на профессиональный ландшафт медицинской отрасли: потребности рынка труда и перспективы развития (анализ зарубежного опыта)</article-title><trans-title-group xml:lang="en"><trans-title>The impact of digitalization on the professional landscape of the medical industry: labor market needs and development prospects (analysis of foreign experience)</trans-title></trans-title-group></title-group><contrib-group><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0003-0098-1403</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Кобякова</surname><given-names>О. С.</given-names></name><name name-style="western" xml:lang="en"><surname>Kobyakova</surname><given-names>O. S.</given-names></name></name-alternatives><bio xml:lang="ru"><p>чл.-корр. РАН, д.м.н.</p><p>г. Москва</p></bio><bio xml:lang="en"><p>Corresponding Member of the RAS, DSc</p><p>Moscow</p></bio><email xlink:type="simple">kobyakovaos@mednet.ru</email><xref ref-type="aff" rid="aff-1"/></contrib><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0001-9612-8815</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Канев</surname><given-names>А. Ф.</given-names></name><name name-style="western" xml:lang="en"><surname>Kanev</surname><given-names>A. F.</given-names></name></name-alternatives><bio xml:lang="ru"><p>к.м.н.</p><p>г. Москва</p></bio><bio xml:lang="en"><p>PhD</p><p>Moscow</p><p> </p></bio><email xlink:type="simple">alexkanev92@gmail.com</email><xref ref-type="aff" rid="aff-2"/></contrib><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0003-1896-6420</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Куракова</surname><given-names>Н. Г.</given-names></name><name name-style="western" xml:lang="en"><surname>Kurakova</surname><given-names>N. G.</given-names></name></name-alternatives><bio xml:lang="ru"><p>д.б.н.</p><p>г. Москва</p></bio><bio xml:lang="en"><p>DSc</p><p>Moscow</p></bio><email xlink:type="simple">idmz@mednet.ru</email><xref ref-type="aff" rid="aff-2"/></contrib><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">https://orcid.org/0009-0006-6567-4235</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Кармина</surname><given-names>Р. Л.</given-names></name><name name-style="western" xml:lang="en"><surname>Karmina</surname><given-names>R. L.</given-names></name></name-alternatives><bio xml:lang="ru"><p>г. Москва</p></bio><bio xml:lang="en"><p>Moscow</p></bio><email xlink:type="simple">r.karmina@yandex.ru</email><xref ref-type="aff" rid="aff-2"/></contrib></contrib-group><aff-alternatives id="aff-1"><aff xml:lang="ru"><institution>ФГБУ «Центральный научно-исследовательский институт организации и информатизации здравоохранения» Министерства здравоохранения Российской Федерации</institution><country>Россия</country></aff><aff xml:lang="en"><institution>Russian Research Institute of Health</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&#13;
здравоохранения» Министерства здравоохранения Российской Федерации</institution><country>Россия</country></aff><aff xml:lang="en"><institution>Russian Research Institute of Health</institution><country>Russian Federation</country></aff></aff-alternatives><pub-date pub-type="collection"><year>2026</year></pub-date><pub-date pub-type="epub"><day>29</day><month>03</month><year>2026</year></pub-date><volume>0</volume><issue>1</issue><fpage>38</fpage><lpage>51</lpage><permissions><copyright-statement>Copyright &amp;#x00A9; Кобякова О.С., Канев А.Ф., Куракова Н.Г., Кармина Р.Л., 2026</copyright-statement><copyright-year>2026</copyright-year><copyright-holder xml:lang="ru">Кобякова О.С., Канев А.Ф., Куракова Н.Г., Кармина Р.Л.</copyright-holder><copyright-holder xml:lang="en">Kobyakova O.S., Kanev A.F., Kurakova N.G., Karmina R.L.</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.vit-j.ru/jour/article/view/311">https://www.vit-j.ru/jour/article/view/311</self-uri><abstract><sec><title>Актуальность</title><p>Актуальность. Внедрение цифровых технологий в систему здравоохранения оказывает глубокое и многовекторное влияние на самую ценную и уязвимую ее составляющую – человеческие ресурсы. Цифровая трансформация меняет ландшафт профессиональной деятельности, инициируя появление принципиально новых специальностей и требований к компетенциям и навыкам медицинских работников.</p></sec><sec><title>Цель исследования</title><p>Цель исследования: систематизировать актуальные данные о влиянии цифровизации на потребность в медицинских кадрах, на изменение профессионального ландшафта и на требования к компетенциям медицинских работников.</p></sec><sec><title>Материалы и методы</title><p>Материалы и методы. Систематически проанализированы зарубежные публикации, извлеченные из баз данных Scopus, PubMed, Google Scholar с использованием поискового образа: «digital technologies» OR «artificial intelligence» or «telemedicine» and «workforce» and «healthcare». Включались все типы исследований, оценивающих влияние цифровых технологий (искусственный интеллект, телемедицина, роботизация, интернет медицинских вещей и анализ больших данных) на уровень нагрузки на медперсонал.</p></sec><sec><title>Результаты</title><p>Результаты. В обзор вошла 61 зарубежная публикация, позволяющая отметить, что по состоянию на конец 2025 г. цифровые технологии не предлагают глобальной системе здравоохранения решения проблемы кадрового дефицита, но предоставляют комплекс инструментов, позволяющих ей функционировать более эффективно, устойчиво и качественно даже в условиях объективного глобального дефицита человеческих ресурсов. Поэтому цифровизация в большинстве публикаций, вошедших в обзор, рассматривается в качестве ключевого инструмента смягчения последствий глобального кадрового дефицита.</p></sec><sec><title>Заключение</title><p>Заключение. Выполненный обзор обозначил перспективу глубинной трансформации ландшафта медицинских профессий. Роли врачей и медсестер эволюционируют в сторону управления данными, их критической интерпретации и усиленного взаимодействия с пациентом. Возникает устойчивый спрос на принципиально новые гибридные профессии на стыке медицины, информационных технологий и наук о данных (биоинформатики, разработчики медицинского программного обеспечения, специалисты по кибербезопасности). Для реализации потенциала цифровизации необходимы преодоление нормативных барьеров и значительная трансформация системы медицинского образования.</p></sec></abstract><trans-abstract xml:lang="en"><sec><title>Significance</title><p>Significance. The introduction of digital technologies into the healthcare system has a profound and multidimensional impact on its most valuable and vulnerable component - human resources. Digital transformation is changing the landscape of professional activity, leading to the emergence of fundamentally new specialties and requirements for competencies and skills of medical professionals.</p></sec><sec><title>Aim</title><p>Aim: to systematize current data on the impact of digitalization on the demand for medical personnel, the changing professional landscape, and the requirements for the competencies of medical professionals.</p></sec><sec><title>Materials and methods</title><p>Materials and methods. We systematically analyzed international publications retrieved from Scopus, PubMed, and Google Scholar using the search terms "digital technologies," "artificial intelligence," or "telemedicine," "workforce," and "healthcare.". All types of studies assessing the impact of digital technologies (artificial intelligence, telemedicine, robotics, the Internet of Medical Things, and big data analysis) on the workload of medical staff were included.</p></sec><sec><title>Results</title><p>Results. The review includes 61 international publications, which indicate that, as of the end of 2025, digital technologies do not offer the global healthcare system a solution to the workforce shortage. Instead, they provide a set of tools enabling it to function more efficiently, sustainably, and efficiently, even in the face of an objective global human resource shortage. Therefore, digitalization is considered a key tool in mitigating the consequences of the global workforce shortage in the majority of publications included in the review.</p></sec><sec><title>Conclusion</title><p>Conclusion. The review highlights the potential for a profound transformation of the medical profession landscape. physicians and nurses are evolving toward data management, critical interpretation, and enhanced patient engagement. There is a strong demand for fundamentally new hybrid professions at the intersection of medicine, information technology, and data science (bioinformaticians, medical software developers, cybersecurity specialists). Realizing the potential of digitalization requires overcoming regulatory barriers and significantly transforming the medical education system.</p></sec></trans-abstract><kwd-group xml:lang="ru"><kwd>цифровая трансформация</kwd><kwd>система здравоохранения</kwd><kwd>кадровое обеспечение</kwd><kwd>искусственный интеллект</kwd><kwd>телемедицина</kwd><kwd>роботизация</kwd><kwd>интернет медицинских вещей</kwd><kwd>экономическая эффективность</kwd><kwd>межлицензионная практика</kwd><kwd>модели оплаты</kwd><kwd>ответственность за решения</kwd><kwd>интероперабельность</kwd></kwd-group><kwd-group xml:lang="en"><kwd>digital transformation</kwd><kwd>healthcare system</kwd><kwd>human resources</kwd><kwd>artificial intelligence</kwd><kwd>telemedicine</kwd><kwd>robotics</kwd><kwd>Internet of medical things</kwd><kwd>economic efficiency</kwd><kwd>inter-license practices</kwd><kwd>payment models</kwd><kwd>responsibility for decisions</kwd><kwd>interoperability</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">Socha-Dietrich, K. Empowering the health workforce to make the most of the digital revolution. OECD Health Working Papers. 2021; 129. doi: 10.1787/37ff0eaa-en.</mixed-citation><mixed-citation xml:lang="en">Socha-Dietrich, K. Empowering the health workforce to make the most of the digital revolution. OECD Health Working Papers. 2021; 129. doi: 10.1787/37ff0eaa-en.</mixed-citation></citation-alternatives></ref><ref id="cit2"><label>2</label><citation-alternatives><mixed-citation xml:lang="ru">WHO guideline on health workforce development, attraction, recruitment and retention in rural and remote areas. 10.09.2025.</mixed-citation><mixed-citation xml:lang="en">WHO guideline on health workforce development, attraction, recruitment and retention in rural and remote areas. 10.09.2025.</mixed-citation></citation-alternatives></ref><ref id="cit3"><label>3</label><citation-alternatives><mixed-citation xml:lang="ru">Ag Ahmed MA, Diakité SL, Sissoko K, Gagnon MP, Charron S. Factors explaining the shortage and poor retention of qualified health workers in rural and remote areas of the Kayes, region of Mali: a qualitative study. Rural Remote Health. 2020; 20(3):5772. doi: 10.22605/RRH5772.</mixed-citation><mixed-citation xml:lang="en">Ag Ahmed MA, Diakité SL, Sissoko K, Gagnon MP, Charron S. Factors explaining the shortage and poor retention of qualified health workers in rural and remote areas of the Kayes, region of Mali: a qualitative study. Rural Remote Health. 2020; 20(3):5772. doi: 10.22605/RRH5772.</mixed-citation></citation-alternatives></ref><ref id="cit4"><label>4</label><citation-alternatives><mixed-citation xml:lang="ru">Yeung AWK, Torkamani A, Butte AJ, et al. The promise of digital healthcare technologies. Front Public Health. 2023; 11: 1196596. doi: 10.3389/fpubh.2023.1196596.</mixed-citation><mixed-citation xml:lang="en">Yeung AWK, Torkamani A, Butte AJ, et al. The promise of digital healthcare technologies. Front Public Health. 2023; 11: 1196596. doi: 10.3389/fpubh.2023.1196596.</mixed-citation></citation-alternatives></ref><ref id="cit5"><label>5</label><citation-alternatives><mixed-citation xml:lang="ru">Al-Saleem AI, Aldakheel MK. Barriers to Workforce-Driven Innovation in Healthcare. Cureus. 2024; 16(10): e72316. doi: 10.7759/cureus.72316.</mixed-citation><mixed-citation xml:lang="en">Al-Saleem AI, Aldakheel MK. Barriers to Workforce-Driven Innovation in Healthcare. Cureus. 2024; 16(10): e72316. doi: 10.7759/cureus.72316.</mixed-citation></citation-alternatives></ref><ref id="cit6"><label>6</label><citation-alternatives><mixed-citation xml:lang="ru">Al-Haimi B, Ali F, Hujainah F. Digital Transformation in Healthcare: Impact on Organizations' Strategies, Future Landscape, and Required Skills. In: Navigating the Intersection of Business, Sustainability and Technology. Contributions to Environmental Sciences &amp; Innovative Business Technology. Springer, Singapore. 2023. doi: 10.1007/978-981-99-8572-2_3.</mixed-citation><mixed-citation xml:lang="en">Al-Haimi B, Ali F, Hujainah F. Digital Transformation in Healthcare: Impact on Organizations' Strategies, Future Landscape, and Required Skills. In: Navigating the Intersection of Business, Sustainability and Technology. Contributions to Environmental Sciences &amp; Innovative Business Technology. Springer, Singapore. 2023. doi: 10.1007/978-981-99-8572-2_3.</mixed-citation></citation-alternatives></ref><ref id="cit7"><label>7</label><citation-alternatives><mixed-citation xml:lang="ru">Jeilani A, Hussein A. Impact of digital health technologies adoption on healthcare workers’ performance and workload: perspective with DOI and TOE models. BMC Health Serv Res 25, 271(2025). doi: 10.1186/s12913-025-12414-4.</mixed-citation><mixed-citation xml:lang="en">Jeilani A, Hussein A. Impact of digital health technologies adoption on healthcare workers’ performance and workload: perspective with DOI and TOE models. BMC Health Serv Res 25, 271(2025). doi: 10.1186/s12913-025-12414-4.</mixed-citation></citation-alternatives></ref><ref id="cit8"><label>8</label><citation-alternatives><mixed-citation xml:lang="ru">Mohd J, Abid H, Ravi PS. Health informatics to enhance the healthcare industry's culture: An extensive analysis of its features, contributions, applications and limitations. Informatics and Health. 2024; 1(2): 123-148. doi: 10.1016/j.infoh.2024.05.001.</mixed-citation><mixed-citation xml:lang="en">Mohd J, Abid H, Ravi PS. Health informatics to enhance the healthcare industry's culture: An extensive analysis of its features, contributions, applications and limitations. Informatics and Health. 2024; 1(2): 123-148. doi: 10.1016/j.infoh.2024.05.001.</mixed-citation></citation-alternatives></ref><ref id="cit9"><label>9</label><citation-alternatives><mixed-citation xml:lang="ru">Zheng T, Lin F, Li X, et al. Deep learning-enabled fully automated pipeline system for segmentation and classification of single-mass breast lesions using contrast-enhanced mammography: a prospective, multicentre study. EClinicalMedicine. 2023; 58: 101913. doi: 10.1016/j.eclinm.2023.101913.</mixed-citation><mixed-citation xml:lang="en">Zheng T, Lin F, Li X, et al. Deep learning-enabled fully automated pipeline system for segmentation and classification of single-mass breast lesions using contrast-enhanced mammography: a prospective, multicentre study. EClinicalMedicine. 2023; 58: 101913. doi: 10.1016/j.eclinm.2023.101913.</mixed-citation></citation-alternatives></ref><ref id="cit10"><label>10</label><citation-alternatives><mixed-citation xml:lang="ru">Raya-Povedano JL, Romero-Martín S, Elías-Cabot E, et al. AI-based Strategies to Reduce Workload in Breast Cancer Screening with Mammography and Tomosynthesis: A Retrospective Evaluation. Radiology. 2021; 300(1): 57-65. doi: 10.1148/radiol.2021203555.</mixed-citation><mixed-citation xml:lang="en">Raya-Povedano JL, Romero-Martín S, Elías-Cabot E, et al. AI-based Strategies to Reduce Workload in Breast Cancer Screening with Mammography and Tomosynthesis: A Retrospective Evaluation. Radiology. 2021; 300(1): 57-65. doi: 10.1148/radiol.2021203555.</mixed-citation></citation-alternatives></ref><ref id="cit11"><label>11</label><citation-alternatives><mixed-citation xml:lang="ru">Yacoub B, Varga-Szemes A, Schoepf UJ, et al. Impact of Artificial Intelligence Assistance on Chest CT Interpretation Times: A Prospective Randomized Study. AJR Am J Roentgenol. 2022; 219(5): 743-751. doi: 10.2214/AJR.22.27598.</mixed-citation><mixed-citation xml:lang="en">Yacoub B, Varga-Szemes A, Schoepf UJ, et al. Impact of Artificial Intelligence Assistance on Chest CT Interpretation Times: A Prospective Randomized Study. AJR Am J Roentgenol. 2022; 219(5): 743-751. doi: 10.2214/AJR.22.27598.</mixed-citation></citation-alternatives></ref><ref id="cit12"><label>12</label><citation-alternatives><mixed-citation xml:lang="ru">Li N, Wu Z, Jiang C, Sun L, et al. An automatic fresh rib fracture detection and positioning system using deep learning. Br J Radiol. 2023; 96(1146): 20221006. doi: 10.1259/bjr.20221006.</mixed-citation><mixed-citation xml:lang="en">Li N, Wu Z, Jiang C, Sun L, et al. An automatic fresh rib fracture detection and positioning system using deep learning. Br J Radiol. 2023; 96(1146): 20221006. doi: 10.1259/bjr.20221006.</mixed-citation></citation-alternatives></ref><ref id="cit13"><label>13</label><citation-alternatives><mixed-citation xml:lang="ru">Shi Z, Miao C, Schoepf UJ, et al. A clinically applicable deep-learning model for detecting intracranial aneurysm in computed tomography angiography images. Nat Commun. 2020; 11(1): 6090. doi: 10.1038/s41467-020-19527-w.</mixed-citation><mixed-citation xml:lang="en">Shi Z, Miao C, Schoepf UJ, et al. A clinically applicable deep-learning model for detecting intracranial aneurysm in computed tomography angiography images. Nat Commun. 2020; 11(1): 6090. doi: 10.1038/s41467-020-19527-w.</mixed-citation></citation-alternatives></ref><ref id="cit14"><label>14</label><citation-alternatives><mixed-citation xml:lang="ru">Ni Q, Sun ZY, Qi L, et al. A deep learning approach to characterize 2019 coronavirus disease (COVID-19) pneumonia in chest CT images. Eur Radiol. 2020; 30(12): 6517-6527. doi: 10.1007/s00330-020-07044-9.</mixed-citation><mixed-citation xml:lang="en">Ni Q, Sun ZY, Qi L, et al. A deep learning approach to characterize 2019 coronavirus disease (COVID-19) pneumonia in chest CT images. Eur Radiol. 2020; 30(12): 6517-6527. doi: 10.1007/s00330-020-07044-9.</mixed-citation></citation-alternatives></ref><ref id="cit15"><label>15</label><citation-alternatives><mixed-citation xml:lang="ru">Lancaster HL, Zheng S, Aleshina OO, et al. Outstanding negative prediction performance of solid pulmonary nodule volume AI for ultra-LDCT baseline lung cancer screening risk stratification. Lung Cancer. 2022; 165: 133-140. doi: 10.1016/j.lungcan.2022.01.002.</mixed-citation><mixed-citation xml:lang="en">Lancaster HL, Zheng S, Aleshina OO, et al. Outstanding negative prediction performance of solid pulmonary nodule volume AI for ultra-LDCT baseline lung cancer screening risk stratification. Lung Cancer. 2022; 165: 133-140. doi: 10.1016/j.lungcan.2022.01.002.</mixed-citation></citation-alternatives></ref><ref id="cit16"><label>16</label><citation-alternatives><mixed-citation xml:lang="ru">Wenderott K, Krups J, Luetkens JA, et al. Prospective effects of an artificial intelligence-based computeraided detection system for prostate imaging on routine workflow and radiologists' outcomes. Eur J Radiol. 2024; 170: 111252. doi: 10.1016/j.ejrad.2023.111252.</mixed-citation><mixed-citation xml:lang="en">Wenderott K, Krups J, Luetkens JA, et al. Prospective effects of an artificial intelligence-based computeraided detection system for prostate imaging on routine workflow and radiologists' outcomes. Eur J Radiol. 2024; 170: 111252. doi: 10.1016/j.ejrad.2023.111252.</mixed-citation></citation-alternatives></ref><ref id="cit17"><label>17</label><citation-alternatives><mixed-citation xml:lang="ru">Yang R, Yan C, Lu S, et al. Tracking cancer lesions on surgical samples of gastric cancer by artificial intelligent algorithms. J Cancer. 2021; 12: 6473-83.</mixed-citation><mixed-citation xml:lang="en">Yang R, Yan C, Lu S, et al. Tracking cancer lesions on surgical samples of gastric cancer by artificial intelligent algorithms. J Cancer. 2021; 12: 6473-83.</mixed-citation></citation-alternatives></ref><ref id="cit18"><label>18</label><citation-alternatives><mixed-citation xml:lang="ru">Eloy C, Marques A, Pinto J, et al. Artificial intelligence-assisted cancer diagnosis improves the efficiency of pathologists in prostatic biopsies. Virchows Arch. 2023; 482: 595-604.</mixed-citation><mixed-citation xml:lang="en">Eloy C, Marques A, Pinto J, et al. Artificial intelligence-assisted cancer diagnosis improves the efficiency of pathologists in prostatic biopsies. Virchows Arch. 2023; 482: 595-604.</mixed-citation></citation-alternatives></ref><ref id="cit19"><label>19</label><citation-alternatives><mixed-citation xml:lang="ru">Peltola J, Basnyat P, Armand Larsen S, et al. Semiautomated classification of nocturnal seizures using video recordings. Epilepsia. 2023; 64(Suppl 4): S65-71.</mixed-citation><mixed-citation xml:lang="en">Peltola J, Basnyat P, Armand Larsen S, et al. Semiautomated classification of nocturnal seizures using video recordings. Epilepsia. 2023; 64(Suppl 4): S65-71.</mixed-citation></citation-alternatives></ref><ref id="cit20"><label>20</label><citation-alternatives><mixed-citation xml:lang="ru">Katz BZ, Feldman MD, Tessema M, et al. Evaluation of Scopio Labs X100 Full Field PBS: the first highresolution full field viewing of peripheral blood specimens combined with artificial intelligence-based morphological analysis. Int J Lab Hematol. 2021; 43: 1408-16.</mixed-citation><mixed-citation xml:lang="en">Katz BZ, Feldman MD, Tessema M, et al. Evaluation of Scopio Labs X100 Full Field PBS: the first highresolution full field viewing of peripheral blood specimens combined with artificial intelligence-based morphological analysis. Int J Lab Hematol. 2021; 43: 1408-16.</mixed-citation></citation-alternatives></ref><ref id="cit21"><label>21</label><citation-alternatives><mixed-citation xml:lang="ru">Yan Y, Jiang W, Zhou Y, et al. Evaluation of a computer-aided diagnostic model for corneal diseases by analyzing in vivo confocal microscopy images. Front Med (Lausanne). 2023; 10: 1164188.</mixed-citation><mixed-citation xml:lang="en">Yan Y, Jiang W, Zhou Y, et al. Evaluation of a computer-aided diagnostic model for corneal diseases by analyzing in vivo confocal microscopy images. Front Med (Lausanne). 2023; 10: 1164188.</mixed-citation></citation-alternatives></ref><ref id="cit22"><label>22</label><citation-alternatives><mixed-citation xml:lang="ru">Yang Y, Pan J, Yuan M, et al. Performance of the AIDRScreening system in detecting diabetic retinopathy in the fundus photographs of Chinese patients: a prospective, multicenter, clinical study. Ann Transl Med. 2022; 10: 1088.</mixed-citation><mixed-citation xml:lang="en">Yang Y, Pan J, Yuan M, et al. Performance of the AIDRScreening system in detecting diabetic retinopathy in the fundus photographs of Chinese patients: a prospective, multicenter, clinical study. Ann Transl Med. 2022; 10: 1088.</mixed-citation></citation-alternatives></ref><ref id="cit23"><label>23</label><citation-alternatives><mixed-citation xml:lang="ru">Tancredi C, Ibba S, Fantesini A, et al. Capturing patient voices: A focus group-based study unveiling the potential of AI in medical diagnosis. Human Technology. 2024; 20(3): 541-557. doi: 10.14254/1795-6889.2024.20-3.6.</mixed-citation><mixed-citation xml:lang="en">Tancredi C, Ibba S, Fantesini A, et al. Capturing patient voices: A focus group-based study unveiling the potential of AI in medical diagnosis. Human Technology. 2024; 20(3): 541-557. doi: 10.14254/1795-6889.2024.20-3.6.</mixed-citation></citation-alternatives></ref><ref id="cit24"><label>24</label><citation-alternatives><mixed-citation xml:lang="ru">Alì M, Fantesini A, Morcella MT, et al. Adoption of AI in Oncological Imaging: Ethical, Regulatory, and Medical-Legal Challenges. Critical Reviews™ in Oncogenesis. 2024; 29(2).</mixed-citation><mixed-citation xml:lang="en">Alì M, Fantesini A, Morcella MT, et al. Adoption of AI in Oncological Imaging: Ethical, Regulatory, and Medical-Legal Challenges. Critical Reviews™ in Oncogenesis. 2024; 29(2).</mixed-citation></citation-alternatives></ref><ref id="cit25"><label>25</label><citation-alternatives><mixed-citation xml:lang="ru">Bongurala AR, Save D, Virmani A, Kashyap R. Transforming health care with artificial intelligence: redefining medical documentation. Mayo Clin Proc Digit Health. 2024; 2(3): 342-347.</mixed-citation><mixed-citation xml:lang="en">Bongurala AR, Save D, Virmani A, Kashyap R. Transforming health care with artificial intelligence: redefining medical documentation. Mayo Clin Proc Digit Health. 2024; 2(3): 342-347.</mixed-citation></citation-alternatives></ref><ref id="cit26"><label>26</label><citation-alternatives><mixed-citation xml:lang="ru">Căvescu AM, Popescu N. Predictive Analytics in Human Resources Management: Evaluating AIHR’s Role in Talent Retention. AppliedMath. 2025; 5: 99. doi: 10.3390/appliedmath5030099.</mixed-citation><mixed-citation xml:lang="en">Căvescu AM, Popescu N. Predictive Analytics in Human Resources Management: Evaluating AIHR’s Role in Talent Retention. AppliedMath. 2025; 5: 99. doi: 10.3390/appliedmath5030099.</mixed-citation></citation-alternatives></ref><ref id="cit27"><label>27</label><citation-alternatives><mixed-citation xml:lang="ru">Fraser Health Advances AI in Healthcare with Digital Navigator and Scheduling Innovations. https://www.startupecosystem.ca/news/fraser-health-advances-ai-in-healthcare-with-digital-navigator-andscheduling-innovations/</mixed-citation><mixed-citation xml:lang="en">Fraser Health Advances AI in Healthcare with Digital Navigator and Scheduling Innovations. https://www.startupecosystem.ca/news/fraser-health-advances-ai-in-healthcare-with-digital-navigator-andscheduling-innovations/</mixed-citation></citation-alternatives></ref><ref id="cit28"><label>28</label><citation-alternatives><mixed-citation xml:lang="ru">Ministry of Health Israel. Government of Israel, Ministry of Health. National Plan for Digital. https://www.health.gov.il/About/projects/DigitalHealth/Pages/default.aspx.</mixed-citation><mixed-citation xml:lang="en">Ministry of Health Israel. Government of Israel, Ministry of Health. National Plan for Digital. https://www.health.gov.il/About/projects/DigitalHealth/Pages/default.aspx.</mixed-citation></citation-alternatives></ref><ref id="cit29"><label>29</label><citation-alternatives><mixed-citation xml:lang="ru">Rojas SL, Ashok M, Morss DyS, et al. Contextual Frameworks for Research on the Implementation of Complex System Interventions [Internet]. Rockville (MD): Agency for Healthcare Research and Quality (US). 2014 Mar. Patient-Centered Medical Home Framework. https://www.ncbi.nlm.nih.gov/books/NBK196203/</mixed-citation><mixed-citation xml:lang="en">Rojas SL, Ashok M, Morss DyS, et al. Contextual Frameworks for Research on the Implementation of Complex System Interventions [Internet]. Rockville (MD): Agency for Healthcare Research and Quality (US). 2014 Mar. Patient-Centered Medical Home Framework. https://www.ncbi.nlm.nih.gov/books/NBK196203/</mixed-citation></citation-alternatives></ref><ref id="cit30"><label>30</label><citation-alternatives><mixed-citation xml:lang="ru">Stoumpos AI, Kitsios F, Talias MA. Digital Transformation in Healthcare: Technology Acceptance and Its Applications. Int J Environ Res Public Health. 2023; 20(4): 3407. doi: 10.3390/ijerph20043407.</mixed-citation><mixed-citation xml:lang="en">Stoumpos AI, Kitsios F, Talias MA. Digital Transformation in Healthcare: Technology Acceptance and Its Applications. Int J Environ Res Public Health. 2023; 20(4): 3407. doi: 10.3390/ijerph20043407.</mixed-citation></citation-alternatives></ref><ref id="cit31"><label>31</label><citation-alternatives><mixed-citation xml:lang="ru">Liu X, Keane PA, Denniston AK. Time to regenerate: the doctor in the age of artificial intelligence. J R Soc Med. 2018; 111(4): 113-116. doi: 10.1177/0141076818762648.</mixed-citation><mixed-citation xml:lang="en">Liu X, Keane PA, Denniston AK. Time to regenerate: the doctor in the age of artificial intelligence. J R Soc Med. 2018; 111(4): 113-116. doi: 10.1177/0141076818762648.</mixed-citation></citation-alternatives></ref><ref id="cit32"><label>32</label><citation-alternatives><mixed-citation xml:lang="ru">https://medical.sectra.com/case/ai-frees-up-valuable-time-for-radiologists-in-a-swedish-healthcareregion/</mixed-citation><mixed-citation xml:lang="en">https://medical.sectra.com/case/ai-frees-up-valuable-time-for-radiologists-in-a-swedish-healthcareregion/</mixed-citation></citation-alternatives></ref><ref id="cit33"><label>33</label><citation-alternatives><mixed-citation xml:lang="ru">Qure.ai impact stories. The impact of AI at The Royal Bolton NHS Hospital, UK. https://www.qure.ai/impact_stories/the-impact-of-ai-at-the-royal-bolton-nhs-hospital-uk.</mixed-citation><mixed-citation xml:lang="en">Qure.ai impact stories. The impact of AI at The Royal Bolton NHS Hospital, UK. https://www.qure.ai/impact_stories/the-impact-of-ai-at-the-royal-bolton-nhs-hospital-uk.</mixed-citation></citation-alternatives></ref><ref id="cit34"><label>34</label><citation-alternatives><mixed-citation xml:lang="ru">Qure.ai impact stories. On Ground with IHVN and Fujifilm in Nigeria. https://www.qure.ai/impact_stories/on-ground-with-ihvn-and-fujifilm-in-nigeria.</mixed-citation><mixed-citation xml:lang="en">Qure.ai impact stories. On Ground with IHVN and Fujifilm in Nigeria. https://www.qure.ai/impact_stories/on-ground-with-ihvn-and-fujifilm-in-nigeria.</mixed-citation></citation-alternatives></ref><ref id="cit35"><label>35</label><citation-alternatives><mixed-citation xml:lang="ru">Zou FW, Tang YF, Liu CY, Ma JA, Hu CH. Concordance Study Between IBM Watson for Oncology and Real Clinical Practice for Cervical Cancer Patients in China: A Retrospective Analysis. Front Genet. 2020; 11: 200. doi: 10.3389/fgene.2020.00200.</mixed-citation><mixed-citation xml:lang="en">Zou FW, Tang YF, Liu CY, Ma JA, Hu CH. Concordance Study Between IBM Watson for Oncology and Real Clinical Practice for Cervical Cancer Patients in China: A Retrospective Analysis. Front Genet. 2020; 11: 200. doi: 10.3389/fgene.2020.00200.</mixed-citation></citation-alternatives></ref><ref id="cit36"><label>36</label><citation-alternatives><mixed-citation xml:lang="ru">Siemens Healthineers. «Облачное решение teamplay — приложения для управления производительностью». https://www.siemens-healthineers.com/ru/digital-health-solutions/digital-solutionsoverview/service-line-managment-solutions/teamplay.</mixed-citation><mixed-citation xml:lang="en">Siemens Healthineers. «Облачное решение teamplay — приложения для управления производительностью». https://www.siemens-healthineers.com/ru/digital-health-solutions/digital-solutionsoverview/service-line-managment-solutions/teamplay.</mixed-citation></citation-alternatives></ref><ref id="cit37"><label>37</label><citation-alternatives><mixed-citation xml:lang="ru">Suki.ai. The AI infrastructure for halthcare. https://www.suki.ai/</mixed-citation><mixed-citation xml:lang="en">Suki.ai. The AI infrastructure for halthcare. https://www.suki.ai/</mixed-citation></citation-alternatives></ref><ref id="cit38"><label>38</label><citation-alternatives><mixed-citation xml:lang="ru">BD Pyxis MedStation ES System. Automated dispensing cabinet for single and multi-facilities medication management. https://www.bd.com/en-uk/products-and-solutions/products/productfamilies/bd-pyxis-medstation-es-system.</mixed-citation><mixed-citation xml:lang="en">BD Pyxis MedStation ES System. Automated dispensing cabinet for single and multi-facilities medication management. https://www.bd.com/en-uk/products-and-solutions/products/productfamilies/bd-pyxis-medstation-es-system.</mixed-citation></citation-alternatives></ref><ref id="cit39"><label>39</label><citation-alternatives><mixed-citation xml:lang="ru">Jung YY, Walsh Á, Patel J, Lai K. Benefits and challenges associated with implementation and ongoing use of automated dispensing cabinet for medicines: a scoping review. Explor Res Clin Soc Pharm. 2025; 18: 100599.</mixed-citation><mixed-citation xml:lang="en">Jung YY, Walsh Á, Patel J, Lai K. Benefits and challenges associated with implementation and ongoing use of automated dispensing cabinet for medicines: a scoping review. Explor Res Clin Soc Pharm. 2025; 18: 100599.</mixed-citation></citation-alternatives></ref><ref id="cit40"><label>40</label><citation-alternatives><mixed-citation xml:lang="ru">Philips eCareCoordinator Clinical dashboard for ambulatory health. https://www.philips.cz/healthcare/product/HCNOCTN482/ecarecoordinator-clinical-dashboard-for-ambulatory-health.</mixed-citation><mixed-citation xml:lang="en">Philips eCareCoordinator Clinical dashboard for ambulatory health. https://www.philips.cz/healthcare/product/HCNOCTN482/ecarecoordinator-clinical-dashboard-for-ambulatory-health.</mixed-citation></citation-alternatives></ref><ref id="cit41"><label>41</label><citation-alternatives><mixed-citation xml:lang="ru">Global strategy on digital health 2020-2025. Geneva: World Health Organization; 2021.</mixed-citation><mixed-citation xml:lang="en">Global strategy on digital health 2020-2025. Geneva: World Health Organization; 2021.</mixed-citation></citation-alternatives></ref><ref id="cit42"><label>42</label><citation-alternatives><mixed-citation xml:lang="ru">Whitepaper “unlocking healthcare's future: the invaluable role of clinical informatics”. https://www. imss.org/sites/hde/files/media/file/2024/04/18/wp_value-of-clinical-informatics-1.pdf.</mixed-citation><mixed-citation xml:lang="en">Whitepaper “unlocking healthcare's future: the invaluable role of clinical informatics”. https://www. imss.org/sites/hde/files/media/file/2024/04/18/wp_value-of-clinical-informatics-1.pdf.</mixed-citation></citation-alternatives></ref><ref id="cit43"><label>43</label><citation-alternatives><mixed-citation xml:lang="ru">Gyldenkærne C, Hansen JU, Hertzum M, Mønsted T. Innovation tactics for implementing an ML application in healthcare: a long and winding road. Int J Hum Comput Stud. 2024; 181: 103162</mixed-citation><mixed-citation xml:lang="en">Gyldenkærne C, Hansen JU, Hertzum M, Mønsted T. Innovation tactics for implementing an ML application in healthcare: a long and winding road. Int J Hum Comput Stud. 2024; 181: 103162</mixed-citation></citation-alternatives></ref><ref id="cit44"><label>44</label><citation-alternatives><mixed-citation xml:lang="ru">Ethics and governance of artificial intelligence for health: WHO guidance. Geneva: World Health Organization; 2021.</mixed-citation><mixed-citation xml:lang="en">Ethics and governance of artificial intelligence for health: WHO guidance. Geneva: World Health Organization; 2021.</mixed-citation></citation-alternatives></ref><ref id="cit45"><label>45</label><citation-alternatives><mixed-citation xml:lang="ru">Topol, E.J. High-performance medicine: the convergence of human and artificial intelligence. Nat Med. 2019; 25: 44-56. doi: 10.1038/s41591-018-0300-7.</mixed-citation><mixed-citation xml:lang="en">Topol, E.J. High-performance medicine: the convergence of human and artificial intelligence. Nat Med. 2019; 25: 44-56. doi: 10.1038/s41591-018-0300-7.</mixed-citation></citation-alternatives></ref><ref id="cit46"><label>46</label><citation-alternatives><mixed-citation xml:lang="ru">https://www.techtarget.com/searchhealthit/definition/clinical-informatics.</mixed-citation><mixed-citation xml:lang="en">https://www.techtarget.com/searchhealthit/definition/clinical-informatics.</mixed-citation></citation-alternatives></ref><ref id="cit47"><label>47</label><citation-alternatives><mixed-citation xml:lang="ru">Hamilton A. The Future of Artificial Intelligence in Surgery. Cureus. 2024; 16(7): e63699. doi: 10.7759/cureus.63699.</mixed-citation><mixed-citation xml:lang="en">Hamilton A. The Future of Artificial Intelligence in Surgery. Cureus. 2024; 16(7): e63699. doi: 10.7759/cureus.63699.</mixed-citation></citation-alternatives></ref><ref id="cit48"><label>48</label><citation-alternatives><mixed-citation xml:lang="ru">Gou F, Liu J, Xiao C, Wu J. Research on artificial-intelligence-assisted medicine: a survey on medical artificial intelligence. Diagnostics (Basel). 2024; 14: 1472.</mixed-citation><mixed-citation xml:lang="en">Gou F, Liu J, Xiao C, Wu J. Research on artificial-intelligence-assisted medicine: a survey on medical artificial intelligence. Diagnostics (Basel). 2024; 14: 1472.</mixed-citation></citation-alternatives></ref><ref id="cit49"><label>49</label><citation-alternatives><mixed-citation xml:lang="ru">Klumpp M, Hintze M, Immonen M, et al. Artificial intelligence for hospital health care: application cases and answers to challenges in European hospitals. Healthcare (Basel). 2021; 9: 961.</mixed-citation><mixed-citation xml:lang="en">Klumpp M, Hintze M, Immonen M, et al. Artificial intelligence for hospital health care: application cases and answers to challenges in European hospitals. Healthcare (Basel). 2021; 9: 961.</mixed-citation></citation-alternatives></ref><ref id="cit50"><label>50</label><citation-alternatives><mixed-citation xml:lang="ru">Closing the digital skills gap in healthcare POLICY BRIEF 72 Identifying core digital skills and competencies and education and training opportunities for health professionals in the European Union. https://eurohealthobservatory.who.int/docs/librariesprovider3/publicationsnew/policybriefbewell-digital-v3-30042025.pdf?sfvrsn=5533673_2.</mixed-citation><mixed-citation xml:lang="en">Closing the digital skills gap in healthcare POLICY BRIEF 72 Identifying core digital skills and competencies and education and training opportunities for health professionals in the European Union. https://eurohealthobservatory.who.int/docs/librariesprovider3/publicationsnew/policybriefbewell-digital-v3-30042025.pdf?sfvrsn=5533673_2.</mixed-citation></citation-alternatives></ref><ref id="cit51"><label>51</label><citation-alternatives><mixed-citation xml:lang="ru">Jose A, Tortorella GL, Vassolo R, Kumar M, Mac Cawley AF. Professional Competence and Its Effect on the Implementation of Healthcare 4.0 Technologies: Scoping Review and Future Research Directions. Int J Environ Res Public Health. 2022; 20(1): 478. doi: 10.3390/ijerph20010478.</mixed-citation><mixed-citation xml:lang="en">Jose A, Tortorella GL, Vassolo R, Kumar M, Mac Cawley AF. Professional Competence and Its Effect on the Implementation of Healthcare 4.0 Technologies: Scoping Review and Future Research Directions. Int J Environ Res Public Health. 2022; 20(1): 478. doi: 10.3390/ijerph20010478.</mixed-citation></citation-alternatives></ref><ref id="cit52"><label>52</label><citation-alternatives><mixed-citation xml:lang="ru">How to Automate Repetitive Tasks in Healthcare. Automation in healthcare industry. https://www.aalpha.net/blog/how-to-automate-repetitive-tasks-in-healthcare/</mixed-citation><mixed-citation xml:lang="en">How to Automate Repetitive Tasks in Healthcare. Automation in healthcare industry. https://www.aalpha.net/blog/how-to-automate-repetitive-tasks-in-healthcare/</mixed-citation></citation-alternatives></ref><ref id="cit53"><label>53</label><citation-alternatives><mixed-citation xml:lang="ru">Yıldırım Ş, Yücekaya AD, Hekimoğlu M, et al. AI-Driven Predictive Maintenance for Workforce and Service Optimization in the Automotive Sector. Appl. Sci. 2025$ 15^ 6282. doi: 10.3390/app15116282.</mixed-citation><mixed-citation xml:lang="en">Yıldırım Ş, Yücekaya AD, Hekimoğlu M, et al. AI-Driven Predictive Maintenance for Workforce and Service Optimization in the Automotive Sector. Appl. Sci. 2025$ 15^ 6282. doi: 10.3390/app15116282.</mixed-citation></citation-alternatives></ref><ref id="cit54"><label>54</label><citation-alternatives><mixed-citation xml:lang="ru">Shahmoradi L, Safdari R, Ahmadi H, Zahmatkeshan M. Clinical decision support systems-based interventions to improve medication outcomes: A systematic literature review on features and effects. Med J Islam Repub Iran. 2021; 35: 27. doi: 10.47176/mjiri.35.27.</mixed-citation><mixed-citation xml:lang="en">Shahmoradi L, Safdari R, Ahmadi H, Zahmatkeshan M. Clinical decision support systems-based interventions to improve medication outcomes: A systematic literature review on features and effects. Med J Islam Repub Iran. 2021; 35: 27. doi: 10.47176/mjiri.35.27.</mixed-citation></citation-alternatives></ref><ref id="cit55"><label>55</label><citation-alternatives><mixed-citation xml:lang="ru">Kakhi K, Jagatheesaperumal SK, Khosravi A, Alizadehsani R, Acharya UR. Fatigue monitoring using wearables and AI: Trends, challenges, and future opportunities. Comput Biol Med. 2025; 195: 110461. doi: 10.1016/j.compbiomed.2025.</mixed-citation><mixed-citation xml:lang="en">Kakhi K, Jagatheesaperumal SK, Khosravi A, Alizadehsani R, Acharya UR. Fatigue monitoring using wearables and AI: Trends, challenges, and future opportunities. Comput Biol Med. 2025; 195: 110461. doi: 10.1016/j.compbiomed.2025.</mixed-citation></citation-alternatives></ref><ref id="cit56"><label>56</label><citation-alternatives><mixed-citation xml:lang="ru">Bernburg M, Gebhardt JS, Groneberg DA, Mache S. Impact of Digitalization in Dentistry on Technostress, Mental Health, and Job Satisfaction: A Quantitative Study. Healthcare (Basel). 2025; 13(1): 72. doi: 10.3390/healthcare13010072.</mixed-citation><mixed-citation xml:lang="en">Bernburg M, Gebhardt JS, Groneberg DA, Mache S. Impact of Digitalization in Dentistry on Technostress, Mental Health, and Job Satisfaction: A Quantitative Study. Healthcare (Basel). 2025; 13(1): 72. doi: 10.3390/healthcare13010072.</mixed-citation></citation-alternatives></ref><ref id="cit57"><label>57</label><citation-alternatives><mixed-citation xml:lang="ru">Biro JM, Handley JL, Malcolm McCurry J, et al. Opportunities and risks of artificial intelligence in patient portal messaging in primary care. NPJ Digit Med. 2025; 8(1): 222. doi: 10.1038/s41746-025-01586-2.</mixed-citation><mixed-citation xml:lang="en">Biro JM, Handley JL, Malcolm McCurry J, et al. Opportunities and risks of artificial intelligence in patient portal messaging in primary care. NPJ Digit Med. 2025; 8(1): 222. doi: 10.1038/s41746-025-01586-2.</mixed-citation></citation-alternatives></ref><ref id="cit58"><label>58</label><citation-alternatives><mixed-citation xml:lang="ru">Wirkkala M, Wijk K, Larsson AC, Engström M. Technology frustration in healthcare - does it matter in staff ratings of stress, emotional exhaustion, and satisfaction with care? A cross-sectional correlational study using the job demands-resources theory. BMC Health Serv Res. 2024; 24(1): 1557. doi: 10.1186/s12913-024-11906-z.</mixed-citation><mixed-citation xml:lang="en">Wirkkala M, Wijk K, Larsson AC, Engström M. Technology frustration in healthcare - does it matter in staff ratings of stress, emotional exhaustion, and satisfaction with care? A cross-sectional correlational study using the job demands-resources theory. BMC Health Serv Res. 2024; 24(1): 1557. doi: 10.1186/s12913-024-11906-z.</mixed-citation></citation-alternatives></ref><ref id="cit59"><label>59</label><citation-alternatives><mixed-citation xml:lang="ru">Board on Health Care Services; Institute of Medicine. The Role of Telehealth in an Evolving Health Care Environment: Workshop Summary. Washington (DC): National Academies Press (US). 2012; 4. Available from: https://www.ncbi.nlm.nih.gov/books/NBK207146/</mixed-citation><mixed-citation xml:lang="en">Board on Health Care Services; Institute of Medicine. The Role of Telehealth in an Evolving Health Care Environment: Workshop Summary. Washington (DC): National Academies Press (US). 2012; 4. Available from: https://www.ncbi.nlm.nih.gov/books/NBK207146/</mixed-citation></citation-alternatives></ref><ref id="cit60"><label>60</label><citation-alternatives><mixed-citation xml:lang="ru">Jones C, Thornton J, Wyatt JC. Artificial intelligence and clinical decision support: clinicians' perspectives on trust, trustworthiness, and liability. Med Law Rev. 2023; 31(4): 501-520. doi: 10.1093/medlaw/fwad013.</mixed-citation><mixed-citation xml:lang="en">Jones C, Thornton J, Wyatt JC. Artificial intelligence and clinical decision support: clinicians' perspectives on trust, trustworthiness, and liability. Med Law Rev. 2023; 31(4): 501-520. doi: 10.1093/medlaw/fwad013.</mixed-citation></citation-alternatives></ref><ref id="cit61"><label>61</label><citation-alternatives><mixed-citation xml:lang="ru">Tolentino R, Baradaran A, Gore G, Pluye P, Abbasgholizadeh-Rahimi S. Curriculum Frameworks and Educational Programs in AI for Medical Students, Residents, and Practicing Physicians: Scoping Review. JMIR Med Educ. 2024; 10: e54793. doi: 10.2196/54793.</mixed-citation><mixed-citation xml:lang="en">Tolentino R, Baradaran A, Gore G, Pluye P, Abbasgholizadeh-Rahimi S. Curriculum Frameworks and Educational Programs in AI for Medical Students, Residents, and Practicing Physicians: Scoping Review. JMIR Med Educ. 2024; 10: e54793. doi: 10.2196/54793.</mixed-citation></citation-alternatives></ref></ref-list><fn-group><fn fn-type="conflict"><p>The authors declare that there are no conflicts of interest present.</p></fn></fn-group></back></article>
