Machine learning research towards combating COVID-19: Virus detection, spread prevention, and medical assistance.
J Biomed Inform
; 117: 103751, 2021 05.
Article
in English
| MEDLINE | ID: covidwho-1152467
ABSTRACT
COVID-19 was first discovered in December 2019 and has continued to rapidly spread across countries worldwide infecting thousands and millions of people. The virus is deadly, and people who are suffering from prior illnesses or are older than the age of 60 are at a higher risk of mortality. Medicine and Healthcare industries have surged towards finding a cure, and different policies have been amended to mitigate the spread of the virus. While Machine Learning (ML) methods have been widely used in other domains, there is now a high demand for ML-aided diagnosis systems for screening, tracking, predicting the spread of COVID-19 and finding a cure against it. In this paper, we present a journey of what role ML has played so far in combating the virus, mainly looking at it from a screening, forecasting, and vaccine perspective. We present a comprehensive survey of the ML algorithms and models that can be used on this expedition and aid with battling the virus.
Keywords
Full text:
Available
Collection:
International databases
Database:
MEDLINE
Main subject:
Machine Learning
/
SARS-CoV-2
/
COVID-19
Type of study:
Diagnostic study
/
Observational study
/
Prognostic study
Topics:
Vaccines
Limits:
Humans
Language:
English
Journal:
J Biomed Inform
Journal subject:
Medical Informatics
Year:
2021
Document Type:
Article
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