2021
DOI: 10.3390/sym14010016
|View full text |Cite
|
Sign up to set email alerts
|

Data-Driven Analytics Leveraging Artificial Intelligence in the Era of COVID-19: An Insightful Review of Recent Developments

Abstract: This paper presents the role of artificial intelligence (AI) and other latest technologies that were employed to fight the recent pandemic (i.e., novel coronavirus disease-2019 (COVID-19)). These technologies assisted the early detection/diagnosis, trends analysis, intervention planning, healthcare burden forecasting, comorbidity analysis, and mitigation and control, to name a few. The key-enablers of these technologies was data that was obtained from heterogeneous sources (i.e., social networks (SN), internet… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
3
1
1

Citation Types

0
8
0

Year Published

2022
2022
2024
2024

Publication Types

Select...
4
4
1

Relationship

0
9

Authors

Journals

citations
Cited by 33 publications
(14 citation statements)
references
References 293 publications
(185 reference statements)
0
8
0
Order By: Relevance
“…The R_Tree operator works similarly to Quinlan's CART or C4.5, with the exception that it chooses a R attributes subset before using them. The subset size is determined by the subset _ratio_parameter and prepruning is a type of pruning that takes place while the tree continues to grow [15][16][17][18][19][20]. As opposed to that, post-pruning is completed once the tree has been produced.…”
Section: Random Tree (Rt)mentioning
confidence: 99%
“…The R_Tree operator works similarly to Quinlan's CART or C4.5, with the exception that it chooses a R attributes subset before using them. The subset size is determined by the subset _ratio_parameter and prepruning is a type of pruning that takes place while the tree continues to grow [15][16][17][18][19][20]. As opposed to that, post-pruning is completed once the tree has been produced.…”
Section: Random Tree (Rt)mentioning
confidence: 99%
“…2. Aritificial intelligence application for fighting against Covid-19 [11] with specific technologies. In to diagnose COVID-19 more quickly, we introduce computer vision technology to quickly help medical staff locate users' lesions and detect infections based on CT and X-ray detection results.…”
Section: Big Data Applicationmentioning
confidence: 99%
“…In addition to compartmental models and statistical models, machine learning models and deep learning models have also been widely used in the COVID-19 forecasting problem [11] , [12] , [13] . In [3] , the authors proposed a logistic growth model for near-term predictions.…”
Section: Introductionmentioning
confidence: 99%