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Early Diagnosis of Type 2 Diabetes Based on Near-Infrared Spectroscopy Combined With Machine Learning and Aquaphotomics

Overview of attention for article published in Frontiers in Chemistry, December 2020
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (51st percentile)
  • Good Attention Score compared to outputs of the same age and source (79th percentile)

Mentioned by

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5 X users

Citations

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16 Dimensions

Readers on

mendeley
38 Mendeley
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Title
Early Diagnosis of Type 2 Diabetes Based on Near-Infrared Spectroscopy Combined With Machine Learning and Aquaphotomics
Published in
Frontiers in Chemistry, December 2020
DOI 10.3389/fchem.2020.580489
Pubmed ID
Authors

Yuanpeng Li, Liu Guo, Li Li, Chuanmei Yang, Peiwen Guang, Furong Huang, Zhenqiang Chen, Lihu Wang, Junhui Hu

X Demographics

X Demographics

The data shown below were collected from the profiles of 5 X users 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 38 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 38 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 4 11%
Student > Doctoral Student 2 5%
Professor > Associate Professor 2 5%
Student > Master 2 5%
Professor 1 3%
Other 3 8%
Unknown 24 63%
Readers by discipline Count As %
Agricultural and Biological Sciences 4 11%
Biochemistry, Genetics and Molecular Biology 2 5%
Physics and Astronomy 2 5%
Engineering 2 5%
Medicine and Dentistry 2 5%
Other 1 3%
Unknown 25 66%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 24 February 2021.
All research outputs
#13,647,584
of 23,267,128 outputs
Outputs from Frontiers in Chemistry
#845
of 6,098 outputs
Outputs of similar age
#241,982
of 508,622 outputs
Outputs of similar age from Frontiers in Chemistry
#67
of 339 outputs
Altmetric has tracked 23,267,128 research outputs across all sources so far. This one is in the 41st percentile – i.e., 41% of other outputs scored the same or lower than it.
So far Altmetric has tracked 6,098 research outputs from this source. They receive a mean Attention Score of 2.1. This one has done well, scoring higher than 85% 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 508,622 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 51% of its contemporaries.
We're also able to compare this research output to 339 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 79% of its contemporaries.