A systematic review on AI/ML approaches against COVID-19 outbreak

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AudienciaPúblico en generales_ES
CoberturaMéxicoes_ES
Fecha de ingreso2026-10-05T16:33:15Z
Fecha de publicación2021-01-01
ResumenA pandemic disease, COVID-19, has caused trouble worldwide by infecting millions of people. The studies that apply artificial intelligence (AI) and machine learning (ML) methods for various purposes against the COVID-19 outbreak have increased because of their significant advantages. Although AI/ML applications provide satisfactory solutions to COVID-19 disease, these solutions can have a wide diversity. This increase in the number of AI/ML studies and diversity in solutions can confuse deciding which AI/ML technique is suitable for which COVID-19 purposes. Because there is no comprehensive review study, this study systematically analyzes and summarizes related studies. A research methodology has been proposed to conduct the systematic literature review for framing the research questions, searching criteria and relevant data extraction. Finally, 264 studies were taken into account after following inclusion and exclusion criteria. This research can be regarded as a key element for epidemic and transmission prediction, diagnosis and detection, and drug/vaccine development. Six research questions are explored with 50 AI/ML approaches in COVID-19, 8 AI/ML methods for patient outcome prediction, 14 AI/ML techniques in disease predictions, along with five AI/ML methods for risk assessment of COVID-19. It also covers AI/ML method in drug development, vaccines for COVID-19, models in COVID-19, datasets and their usage and dataset applications with AI/ML.es_ES
Doihttps://doi.org/10.1007/s40747-021-00424-8es_ES
URIhttps://riuat.uat.edu.mx/handle/123456789/5095
Idiomaenes_ES
EditorialSPRINGER HEIDELBERGes_ES
RelaciónComplex and Intelligent Systemses_ES
URL relacionadohttps://doi.org/10.1007/s40747-021-00424-8es_ES
DerechosAcceso abierto (Metadatos de producción científica)es_ES
Licenciahttp://purl.org/coar/access_right/c_abf2es_ES
FuenteComplex and Intelligent Systems
Palabra claveCOVID-19es_ES
Palabra clavePandemices_ES
Palabra claveArtificial intelligencees_ES
Palabra claveMachine learninges_ES
Palabra claveSystematic reviewes_ES
Palabra claveResearch analysises_ES
TítuloA systematic review on AI/ML approaches against COVID-19 outbreakes_ES
TipoArtículoes_ES
ArbitradoHa sido Arbitradoes_ES
AutorDogan, Onur
AutorTiwari, Sanju
AutorJabbar, M. A.
AutorGuggari, Shankru
AutorDogan, Onures_ES
AutorTiwari, Sanjues_ES
AutorJabbar, M. A.es_ES
AutorGuggari, Shankrues_ES
InstituciónUniversidad Autónoma de Tamaulipas
InstituciónUniversidad Autónoma de Tamaulipases_ES
Número5, SIes_ES
Rango de páginas2655-2678es_ES
URL relacionadahttps://doi.org/10.1007/s40747-021-00424-8
Tipo de artículoIndexado
Tipo de artículoIndexadoes_ES
Volumen7es_ES

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