Artificial Intelligence in the Healthcare System of the Arctic Regions of the Russian Federation
Currently, in the Russian Federation, much attention is paid to the introduction of artificial intelligence technologies into the healthcare system in order to improve the quality of medical care provided. The AI methods support the medical decision-making; it becomes possible to obtain a second opi...
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Northern Arctic Federal University
2023
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Online Access: | https://doi.org/10.37482/issn2221-2698.2023.52.232 https://doaj.org/article/29ef807781064c1986fd7cc6130bf7b2 |
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ftdoajarticles:oai:doaj.org/article:29ef807781064c1986fd7cc6130bf7b2 2023-12-03T10:16:14+01:00 Artificial Intelligence in the Healthcare System of the Arctic Regions of the Russian Federation Lyudmila E. Khaymina Larisa I. Zelenina Evgeniy S. Khaymin Svetlana I. Fedkushova 2023-09-01T00:00:00Z https://doi.org/10.37482/issn2221-2698.2023.52.232 https://doaj.org/article/29ef807781064c1986fd7cc6130bf7b2 EN RU eng rus Northern Arctic Federal University http://arcticandnorth.ru/article_index_years_eng.php?ELEMENT_ID=384584 https://doaj.org/toc/2221-2698 doi:10.37482/issn2221-2698.2023.52.232 2221-2698 https://doaj.org/article/29ef807781064c1986fd7cc6130bf7b2 Арктика и Север, Vol 52, Iss 52, Pp 96-205 (2023) arctic region artificial intelligence healthcare system decision support system neural network machine learning algorithm telemedicine Social Sciences H article 2023 ftdoajarticles https://doi.org/10.37482/issn2221-2698.2023.52.232 2023-11-05T01:38:27Z Currently, in the Russian Federation, much attention is paid to the introduction of artificial intelligence technologies into the healthcare system in order to improve the quality of medical care provided. The AI methods support the medical decision-making; it becomes possible to obtain a second opinion for a doctor when determining a diagnosis, which leads to a reduced risk of determining erroneous diagnoses (including missed pathologies). The development of high-tech medical care is a particularly relevant issue for medical institutions in the Arctic regions, which are geographically distributed and remote territories with hard natural and climatic conditions. The solution of this issue is designed to ensure natural sustaina-ble population growth in these regions and increase the life expectancy of the population of the Russian Arctic, including the indigenous peoples of the North. The article considers the positive experience of cooperation between Russian research centers, medical companies and higher educational institutions in the development and implementation of medical software products based on technologies and methods of artificial intelligence on the example of such Arctic territories of Russia as the Yamalo-Nenets Autonomous Okrug, the Republic of Sakha (Yakutia), the Murmansk Oblast, the Republic of Karelia and the Arkhangelsk Oblast. Article in Journal/Newspaper Arctic Arkhangelsk karelia* Murmansk Oblast nenets Nenets Autonomous Okrug Republic of Karelia Republic of Sakha Yakutia Yamalo Nenets Yamalo-Nenets Autonomous Okrug Arkhangelsk Oblast Directory of Open Access Journals: DOAJ Articles Arctic Murmansk Sakha Arctic and North 52 232 245 |
institution |
Open Polar |
collection |
Directory of Open Access Journals: DOAJ Articles |
op_collection_id |
ftdoajarticles |
language |
English Russian |
topic |
arctic region artificial intelligence healthcare system decision support system neural network machine learning algorithm telemedicine Social Sciences H |
spellingShingle |
arctic region artificial intelligence healthcare system decision support system neural network machine learning algorithm telemedicine Social Sciences H Lyudmila E. Khaymina Larisa I. Zelenina Evgeniy S. Khaymin Svetlana I. Fedkushova Artificial Intelligence in the Healthcare System of the Arctic Regions of the Russian Federation |
topic_facet |
arctic region artificial intelligence healthcare system decision support system neural network machine learning algorithm telemedicine Social Sciences H |
description |
Currently, in the Russian Federation, much attention is paid to the introduction of artificial intelligence technologies into the healthcare system in order to improve the quality of medical care provided. The AI methods support the medical decision-making; it becomes possible to obtain a second opinion for a doctor when determining a diagnosis, which leads to a reduced risk of determining erroneous diagnoses (including missed pathologies). The development of high-tech medical care is a particularly relevant issue for medical institutions in the Arctic regions, which are geographically distributed and remote territories with hard natural and climatic conditions. The solution of this issue is designed to ensure natural sustaina-ble population growth in these regions and increase the life expectancy of the population of the Russian Arctic, including the indigenous peoples of the North. The article considers the positive experience of cooperation between Russian research centers, medical companies and higher educational institutions in the development and implementation of medical software products based on technologies and methods of artificial intelligence on the example of such Arctic territories of Russia as the Yamalo-Nenets Autonomous Okrug, the Republic of Sakha (Yakutia), the Murmansk Oblast, the Republic of Karelia and the Arkhangelsk Oblast. |
format |
Article in Journal/Newspaper |
author |
Lyudmila E. Khaymina Larisa I. Zelenina Evgeniy S. Khaymin Svetlana I. Fedkushova |
author_facet |
Lyudmila E. Khaymina Larisa I. Zelenina Evgeniy S. Khaymin Svetlana I. Fedkushova |
author_sort |
Lyudmila E. Khaymina |
title |
Artificial Intelligence in the Healthcare System of the Arctic Regions of the Russian Federation |
title_short |
Artificial Intelligence in the Healthcare System of the Arctic Regions of the Russian Federation |
title_full |
Artificial Intelligence in the Healthcare System of the Arctic Regions of the Russian Federation |
title_fullStr |
Artificial Intelligence in the Healthcare System of the Arctic Regions of the Russian Federation |
title_full_unstemmed |
Artificial Intelligence in the Healthcare System of the Arctic Regions of the Russian Federation |
title_sort |
artificial intelligence in the healthcare system of the arctic regions of the russian federation |
publisher |
Northern Arctic Federal University |
publishDate |
2023 |
url |
https://doi.org/10.37482/issn2221-2698.2023.52.232 https://doaj.org/article/29ef807781064c1986fd7cc6130bf7b2 |
geographic |
Arctic Murmansk Sakha |
geographic_facet |
Arctic Murmansk Sakha |
genre |
Arctic Arkhangelsk karelia* Murmansk Oblast nenets Nenets Autonomous Okrug Republic of Karelia Republic of Sakha Yakutia Yamalo Nenets Yamalo-Nenets Autonomous Okrug Arkhangelsk Oblast |
genre_facet |
Arctic Arkhangelsk karelia* Murmansk Oblast nenets Nenets Autonomous Okrug Republic of Karelia Republic of Sakha Yakutia Yamalo Nenets Yamalo-Nenets Autonomous Okrug Arkhangelsk Oblast |
op_source |
Арктика и Север, Vol 52, Iss 52, Pp 96-205 (2023) |
op_relation |
http://arcticandnorth.ru/article_index_years_eng.php?ELEMENT_ID=384584 https://doaj.org/toc/2221-2698 doi:10.37482/issn2221-2698.2023.52.232 2221-2698 https://doaj.org/article/29ef807781064c1986fd7cc6130bf7b2 |
op_doi |
https://doi.org/10.37482/issn2221-2698.2023.52.232 |
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Arctic and North |
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52 |
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