Possibilities of information systems for prediction of outcomes of new coronavirus infection COVID-19
The pandemic of coronavirus infection COVID-19 (Coronavirus Disease 2019), caused by a new strain of coronavirus SARSCoV-2 (severe acute respiratory syndrome coronavirus 2), has caused high mortality worldwide. The clinical manifestations of COVID-19 are nonspecific. Diagnostics includes clinica...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | Russian |
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Remedium Group LLC
2022-04-01
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| Series: | Медицинский совет |
| Subjects: | |
| Online Access: | https://www.med-sovet.pro/jour/article/view/6768 |
| _version_ | 1797841887449579520 |
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| author | I. V. Demko E. E. Korchagin O. A. Cherkashin N. V. Gordeeva D. A. Anikin D. A. Anikina |
| author_facet | I. V. Demko E. E. Korchagin O. A. Cherkashin N. V. Gordeeva D. A. Anikin D. A. Anikina |
| author_sort | I. V. Demko |
| collection | DOAJ |
| description | The pandemic of coronavirus infection COVID-19 (Coronavirus Disease 2019), caused by a new strain of coronavirus SARSCoV-2 (severe acute respiratory syndrome coronavirus 2), has caused high mortality worldwide. The clinical manifestations of COVID-19 are nonspecific. Diagnostics includes clinical, laboratory and radiological data. The importance of introducing information systems into medical practice in order to improve the quality of medical care is noted. It is stated that the development of medical artificial intelligence is associated with the development of artificial intelligence programs designed to help the clinic in making a diagnosis, prescribing treatment, as well as predicting the outcome of the disease. Such systems include artificial neural networks, fuzzy expert systems, and hybrid intelligent systems. The article analyzes data from a number of studies on the use of artificial intelligence for diagnosing COVID-19, predicting the risk of mortality and studying risk factors for severe course and lethal outcome in various groups. Using clusters of predictors, models have been developed to predict mortality and understand the relationship of various characteristics and diseases with mortality from COVID-19. The article also summarizes the key factors that worsen the prognosis for COVID-19. Scales for detecting or predicting the development of COVID-19-induced “cytokine storm” are marked as a separate item. |
| first_indexed | 2024-04-09T16:39:52Z |
| format | Article |
| id | doaj.art-2d00b4a30ea14f1695008329d2fd42b0 |
| institution | Directory Open Access Journal |
| issn | 2079-701X 2658-5790 |
| language | Russian |
| last_indexed | 2024-04-09T16:39:52Z |
| publishDate | 2022-04-01 |
| publisher | Remedium Group LLC |
| record_format | Article |
| series | Медицинский совет |
| spelling | doaj.art-2d00b4a30ea14f1695008329d2fd42b02023-04-23T06:56:45ZrusRemedium Group LLCМедицинский совет2079-701X2658-57902022-04-0104425010.21518/2079-701X-2022-16-4-42-506082Possibilities of information systems for prediction of outcomes of new coronavirus infection COVID-19I. V. Demko0E. E. Korchagin1O. A. Cherkashin2N. V. Gordeeva3D. A. Anikin4D. A. Anikina5Krasnoyarsk State Medical University named after Professor V.F. Voino-Yasenetsky; Krasnoyarsk Clinical Regional HospitalKrasnoyarsk Clinical Regional HospitalKrasnoyarsk Clinical Regional HospitalKrasnoyarsk State Medical University named after Professor V.F. Voino-Yasenetsky; Krasnoyarsk Clinical Regional HospitalKrasnoyarsk State Medical University named after Professor V.F. Voino-Yasenetsky; Krasnoyarsk Clinical Regional HospitalKrasnoyarsk State Medical University named after Professor V.F. Voino-YasenetskyThe pandemic of coronavirus infection COVID-19 (Coronavirus Disease 2019), caused by a new strain of coronavirus SARSCoV-2 (severe acute respiratory syndrome coronavirus 2), has caused high mortality worldwide. The clinical manifestations of COVID-19 are nonspecific. Diagnostics includes clinical, laboratory and radiological data. The importance of introducing information systems into medical practice in order to improve the quality of medical care is noted. It is stated that the development of medical artificial intelligence is associated with the development of artificial intelligence programs designed to help the clinic in making a diagnosis, prescribing treatment, as well as predicting the outcome of the disease. Such systems include artificial neural networks, fuzzy expert systems, and hybrid intelligent systems. The article analyzes data from a number of studies on the use of artificial intelligence for diagnosing COVID-19, predicting the risk of mortality and studying risk factors for severe course and lethal outcome in various groups. Using clusters of predictors, models have been developed to predict mortality and understand the relationship of various characteristics and diseases with mortality from COVID-19. The article also summarizes the key factors that worsen the prognosis for COVID-19. Scales for detecting or predicting the development of COVID-19-induced “cytokine storm” are marked as a separate item.https://www.med-sovet.pro/jour/article/view/6768new coronavirus infection covid-19digital technologiesartificial intelligenceneural networksrisk factorsscaleforecasting |
| spellingShingle | I. V. Demko E. E. Korchagin O. A. Cherkashin N. V. Gordeeva D. A. Anikin D. A. Anikina Possibilities of information systems for prediction of outcomes of new coronavirus infection COVID-19 Медицинский совет new coronavirus infection covid-19 digital technologies artificial intelligence neural networks risk factors scale forecasting |
| title | Possibilities of information systems for prediction of outcomes of new coronavirus infection COVID-19 |
| title_full | Possibilities of information systems for prediction of outcomes of new coronavirus infection COVID-19 |
| title_fullStr | Possibilities of information systems for prediction of outcomes of new coronavirus infection COVID-19 |
| title_full_unstemmed | Possibilities of information systems for prediction of outcomes of new coronavirus infection COVID-19 |
| title_short | Possibilities of information systems for prediction of outcomes of new coronavirus infection COVID-19 |
| title_sort | possibilities of information systems for prediction of outcomes of new coronavirus infection covid 19 |
| topic | new coronavirus infection covid-19 digital technologies artificial intelligence neural networks risk factors scale forecasting |
| url | https://www.med-sovet.pro/jour/article/view/6768 |
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