E. Prisciandaro, L. Bertolaccini, L. Spaggiari
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Conclusions: Several artificial intelligence-based approaches have been conceived to ease the pressure on the overloaded health system and assist clinicians in the prognostic profiling of COVID-19 patients. Risk assessment and categorisation are essential: By identifying the more likely subjects to suffer from an acute disease, it might be possible to plan a closer monitoring and/or earlier therapeutic intervention. Hence, artificial intelligence (AI) may support physicians in adjusting their management strategy according to the prognostic estimation, resulting in improved quality of care. This would also facilitate resource allocation in a time when careless supply distribution is not allowed. Artificial intelligence may support physicians in adjusting their management strategy according to the prognostic estimation, resulting in improved quality of care. © 2022 Quantum. All rights reserved.","PeriodicalId":74794,"journal":{"name":"Shanghai chest","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Applications of artificial intelligence to prognostic stratification of COVID-19: a narrative review\",\"authors\":\"E. Prisciandaro, L. Bertolaccini, L. Spaggiari\",\"doi\":\"10.21037/shc-21-17\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Objective: New approaches incorporating artificial intelligence solutions have proven successful and valuable support for decision-making. The purpose of this review is to describe the emerging artificial intelligence applications to the prognostic stratification and profiling of patients suffering from COVID-19. Background: COVID-19 has become a public health emergency, alarming social and economic impact on healthcare systems worldwide. It is paramount to identify patients at the highest risk of developing severe COVID-19, thus improving resource allocation. Methods: A systematic literature search for articles published in English between the date of database inception and January 31, 2021, was performed in EMBASE (via Ovid), MEDLINE (via PubMed) and Cochrane CENTRAL. Conclusions: Several artificial intelligence-based approaches have been conceived to ease the pressure on the overloaded health system and assist clinicians in the prognostic profiling of COVID-19 patients. Risk assessment and categorisation are essential: By identifying the more likely subjects to suffer from an acute disease, it might be possible to plan a closer monitoring and/or earlier therapeutic intervention. Hence, artificial intelligence (AI) may support physicians in adjusting their management strategy according to the prognostic estimation, resulting in improved quality of care. This would also facilitate resource allocation in a time when careless supply distribution is not allowed. Artificial intelligence may support physicians in adjusting their management strategy according to the prognostic estimation, resulting in improved quality of care. © 2022 Quantum. All rights reserved.\",\"PeriodicalId\":74794,\"journal\":{\"name\":\"Shanghai chest\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Shanghai chest\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.21037/shc-21-17\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Shanghai chest","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.21037/shc-21-17","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Applications of artificial intelligence to prognostic stratification of COVID-19: a narrative review
Objective: New approaches incorporating artificial intelligence solutions have proven successful and valuable support for decision-making. The purpose of this review is to describe the emerging artificial intelligence applications to the prognostic stratification and profiling of patients suffering from COVID-19. Background: COVID-19 has become a public health emergency, alarming social and economic impact on healthcare systems worldwide. It is paramount to identify patients at the highest risk of developing severe COVID-19, thus improving resource allocation. Methods: A systematic literature search for articles published in English between the date of database inception and January 31, 2021, was performed in EMBASE (via Ovid), MEDLINE (via PubMed) and Cochrane CENTRAL. Conclusions: Several artificial intelligence-based approaches have been conceived to ease the pressure on the overloaded health system and assist clinicians in the prognostic profiling of COVID-19 patients. Risk assessment and categorisation are essential: By identifying the more likely subjects to suffer from an acute disease, it might be possible to plan a closer monitoring and/or earlier therapeutic intervention. Hence, artificial intelligence (AI) may support physicians in adjusting their management strategy according to the prognostic estimation, resulting in improved quality of care. This would also facilitate resource allocation in a time when careless supply distribution is not allowed. Artificial intelligence may support physicians in adjusting their management strategy according to the prognostic estimation, resulting in improved quality of care. © 2022 Quantum. All rights reserved.