Cargando…
A Comprehensive Review of Machine Learning Used to Combat COVID-19
Coronavirus disease (COVID-19) has had a significant impact on global health since the start of the pandemic in 2019. As of June 2022, over 539 million cases have been confirmed worldwide with over 6.3 million deaths as a result. Artificial Intelligence (AI) solutions such as machine learning and de...
Autores principales: | , , , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9406981/ https://www.ncbi.nlm.nih.gov/pubmed/36010204 http://dx.doi.org/10.3390/diagnostics12081853 |
_version_ | 1784774254293680128 |
---|---|
author | Gomes, Rahul Kamrowski, Connor Langlois, Jordan Rozario, Papia Dircks, Ian Grottodden, Keegan Martinez, Matthew Tee, Wei Zhong Sargeant, Kyle LaFleur, Corbin Haley, Mitchell |
author_facet | Gomes, Rahul Kamrowski, Connor Langlois, Jordan Rozario, Papia Dircks, Ian Grottodden, Keegan Martinez, Matthew Tee, Wei Zhong Sargeant, Kyle LaFleur, Corbin Haley, Mitchell |
author_sort | Gomes, Rahul |
collection | PubMed |
description | Coronavirus disease (COVID-19) has had a significant impact on global health since the start of the pandemic in 2019. As of June 2022, over 539 million cases have been confirmed worldwide with over 6.3 million deaths as a result. Artificial Intelligence (AI) solutions such as machine learning and deep learning have played a major part in this pandemic for the diagnosis and treatment of COVID-19. In this research, we review these modern tools deployed to solve a variety of complex problems. We explore research that focused on analyzing medical images using AI models for identification, classification, and tissue segmentation of the disease. We also explore prognostic models that were developed to predict health outcomes and optimize the allocation of scarce medical resources. Longitudinal studies were conducted to better understand COVID-19 and its effects on patients over a period of time. This comprehensive review of the different AI methods and modeling efforts will shed light on the role that AI has played and what path it intends to take in the fight against COVID-19. |
format | Online Article Text |
id | pubmed-9406981 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-94069812022-08-26 A Comprehensive Review of Machine Learning Used to Combat COVID-19 Gomes, Rahul Kamrowski, Connor Langlois, Jordan Rozario, Papia Dircks, Ian Grottodden, Keegan Martinez, Matthew Tee, Wei Zhong Sargeant, Kyle LaFleur, Corbin Haley, Mitchell Diagnostics (Basel) Review Coronavirus disease (COVID-19) has had a significant impact on global health since the start of the pandemic in 2019. As of June 2022, over 539 million cases have been confirmed worldwide with over 6.3 million deaths as a result. Artificial Intelligence (AI) solutions such as machine learning and deep learning have played a major part in this pandemic for the diagnosis and treatment of COVID-19. In this research, we review these modern tools deployed to solve a variety of complex problems. We explore research that focused on analyzing medical images using AI models for identification, classification, and tissue segmentation of the disease. We also explore prognostic models that were developed to predict health outcomes and optimize the allocation of scarce medical resources. Longitudinal studies were conducted to better understand COVID-19 and its effects on patients over a period of time. This comprehensive review of the different AI methods and modeling efforts will shed light on the role that AI has played and what path it intends to take in the fight against COVID-19. MDPI 2022-07-31 /pmc/articles/PMC9406981/ /pubmed/36010204 http://dx.doi.org/10.3390/diagnostics12081853 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Review Gomes, Rahul Kamrowski, Connor Langlois, Jordan Rozario, Papia Dircks, Ian Grottodden, Keegan Martinez, Matthew Tee, Wei Zhong Sargeant, Kyle LaFleur, Corbin Haley, Mitchell A Comprehensive Review of Machine Learning Used to Combat COVID-19 |
title | A Comprehensive Review of Machine Learning Used to Combat COVID-19 |
title_full | A Comprehensive Review of Machine Learning Used to Combat COVID-19 |
title_fullStr | A Comprehensive Review of Machine Learning Used to Combat COVID-19 |
title_full_unstemmed | A Comprehensive Review of Machine Learning Used to Combat COVID-19 |
title_short | A Comprehensive Review of Machine Learning Used to Combat COVID-19 |
title_sort | comprehensive review of machine learning used to combat covid-19 |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9406981/ https://www.ncbi.nlm.nih.gov/pubmed/36010204 http://dx.doi.org/10.3390/diagnostics12081853 |
work_keys_str_mv | AT gomesrahul acomprehensivereviewofmachinelearningusedtocombatcovid19 AT kamrowskiconnor acomprehensivereviewofmachinelearningusedtocombatcovid19 AT langloisjordan acomprehensivereviewofmachinelearningusedtocombatcovid19 AT rozariopapia acomprehensivereviewofmachinelearningusedtocombatcovid19 AT dircksian acomprehensivereviewofmachinelearningusedtocombatcovid19 AT grottoddenkeegan acomprehensivereviewofmachinelearningusedtocombatcovid19 AT martinezmatthew acomprehensivereviewofmachinelearningusedtocombatcovid19 AT teeweizhong acomprehensivereviewofmachinelearningusedtocombatcovid19 AT sargeantkyle acomprehensivereviewofmachinelearningusedtocombatcovid19 AT lafleurcorbin acomprehensivereviewofmachinelearningusedtocombatcovid19 AT haleymitchell acomprehensivereviewofmachinelearningusedtocombatcovid19 AT gomesrahul comprehensivereviewofmachinelearningusedtocombatcovid19 AT kamrowskiconnor comprehensivereviewofmachinelearningusedtocombatcovid19 AT langloisjordan comprehensivereviewofmachinelearningusedtocombatcovid19 AT rozariopapia comprehensivereviewofmachinelearningusedtocombatcovid19 AT dircksian comprehensivereviewofmachinelearningusedtocombatcovid19 AT grottoddenkeegan comprehensivereviewofmachinelearningusedtocombatcovid19 AT martinezmatthew comprehensivereviewofmachinelearningusedtocombatcovid19 AT teeweizhong comprehensivereviewofmachinelearningusedtocombatcovid19 AT sargeantkyle comprehensivereviewofmachinelearningusedtocombatcovid19 AT lafleurcorbin comprehensivereviewofmachinelearningusedtocombatcovid19 AT haleymitchell comprehensivereviewofmachinelearningusedtocombatcovid19 |