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Development and economic assessment of machine learning models to predict glycosylated hemoglobin in type 2 diabetes

Overview of attention for article published in Frontiers in Pharmacology, June 2023
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age and source (58th percentile)

Mentioned by

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2 X users

Citations

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2 Dimensions

Readers on

mendeley
17 Mendeley
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Title
Development and economic assessment of machine learning models to predict glycosylated hemoglobin in type 2 diabetes
Published in
Frontiers in Pharmacology, June 2023
DOI 10.3389/fphar.2023.1216182
Pubmed ID
Authors

Yi-Tong Tong, Guang-Jie Gao, Huan Chang, Xing-Wei Wu, Meng-Ting Li

X Demographics

X Demographics

The data shown below were collected from the profiles of 2 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 17 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 17 100%

Demographic breakdown

Readers by professional status Count As %
Other 2 12%
Researcher 2 12%
Unspecified 1 6%
Unknown 12 71%
Readers by discipline Count As %
Medicine and Dentistry 2 12%
Computer Science 2 12%
Unspecified 1 6%
Nursing and Health Professions 1 6%
Unknown 11 65%
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 01 July 2023.
All research outputs
#20,631,149
of 26,215,093 outputs
Outputs from Frontiers in Pharmacology
#8,718
of 20,174 outputs
Outputs of similar age
#265,762
of 380,210 outputs
Outputs of similar age from Frontiers in Pharmacology
#238
of 726 outputs
Altmetric has tracked 26,215,093 research outputs across all sources so far. This one is in the 18th percentile – i.e., 18% of other outputs scored the same or lower than it.
So far Altmetric has tracked 20,174 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one is in the 49th percentile – i.e., 49% 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 380,210 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 26th percentile – i.e., 26% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 726 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 58% of its contemporaries.