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Short-Term Prediction of COVID-19 Using Novel Hybrid Ensemble Empirical Mode Decomposition and Error Trend Seasonal Model

Overview of attention for article published in Frontiers in Public Health, July 2022
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Mentioned by

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1 X user

Citations

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5 Dimensions

Readers on

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9 Mendeley
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Title
Short-Term Prediction of COVID-19 Using Novel Hybrid Ensemble Empirical Mode Decomposition and Error Trend Seasonal Model
Published in
Frontiers in Public Health, July 2022
DOI 10.3389/fpubh.2022.922795
Pubmed ID
Authors

Dost Muhammad Khan, Muhammad Ali, Nadeem Iqbal, Umair Khalil, Hassan M. Aljohani, Amirah Saeed Alharthi, Ahmed Z. Afify

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 9 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 9 100%

Demographic breakdown

Readers by professional status Count As %
Unspecified 1 11%
Student > Ph. D. Student 1 11%
Lecturer 1 11%
Student > Master 1 11%
Unknown 5 56%
Readers by discipline Count As %
Unspecified 1 11%
Environmental Science 1 11%
Engineering 1 11%
Unknown 6 67%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 30 July 2022.
All research outputs
#20,702,072
of 23,302,246 outputs
Outputs from Frontiers in Public Health
#8,008
of 10,811 outputs
Outputs of similar age
#345,190
of 433,800 outputs
Outputs of similar age from Frontiers in Public Health
#966
of 1,261 outputs
Altmetric has tracked 23,302,246 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 10,811 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 9.8. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 433,800 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 1,261 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.