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Chronological Age Prediction: Developmental Evaluation of DNA Methylation-Based Machine Learning Models

Overview of attention for article published in Frontiers in Bioengineering and Biotechnology, January 2022
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (85th percentile)
  • High Attention Score compared to outputs of the same age and source (96th percentile)

Mentioned by

twitter
29 X users

Citations

dimensions_citation
17 Dimensions

Readers on

mendeley
28 Mendeley
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Title
Chronological Age Prediction: Developmental Evaluation of DNA Methylation-Based Machine Learning Models
Published in
Frontiers in Bioengineering and Biotechnology, January 2022
DOI 10.3389/fbioe.2021.819991
Pubmed ID
Authors

Haoliang Fan, Qiqian Xie, Zheng Zhang, Junhao Wang, Xuncai Chen, Pingming Qiu

X Demographics

X Demographics

The data shown below were collected from the profiles of 29 X users who shared this research output. Click here to find out more about how the information was compiled.
As of 1 July 2024, you may notice a temporary increase in the numbers of X profiles with Unknown location. Click here to learn more.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 28 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 28 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 5 18%
Student > Ph. D. Student 3 11%
Student > Master 2 7%
Researcher 2 7%
Unspecified 1 4%
Other 3 11%
Unknown 12 43%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 10 36%
Unspecified 1 4%
Environmental Science 1 4%
Pharmacology, Toxicology and Pharmaceutical Science 1 4%
Agricultural and Biological Sciences 1 4%
Other 2 7%
Unknown 12 43%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 11. 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 11 February 2022.
All research outputs
#3,024,437
of 24,133,587 outputs
Outputs from Frontiers in Bioengineering and Biotechnology
#396
of 7,613 outputs
Outputs of similar age
#73,144
of 505,803 outputs
Outputs of similar age from Frontiers in Bioengineering and Biotechnology
#20
of 585 outputs
Altmetric has tracked 24,133,587 research outputs across all sources so far. Compared to these this one has done well and is in the 87th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,613 research outputs from this source. They receive a mean Attention Score of 3.6. This one has done particularly well, scoring higher than 94% of its peers.
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 505,803 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 85% of its contemporaries.
We're also able to compare this research output to 585 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 96% of its contemporaries.