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Development and validation of a machine learning-augmented algorithm for diabetes screening in community and primary care settings: A population-based study

Overview of attention for article published in Frontiers in endocrinology, November 2022
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1 X user

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12 Mendeley
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Title
Development and validation of a machine learning-augmented algorithm for diabetes screening in community and primary care settings: A population-based study
Published in
Frontiers in endocrinology, November 2022
DOI 10.3389/fendo.2022.1043919
Pubmed ID
Authors

XiaoHuan Liu, Weiyue Zhang, Qiao Zhang, Long Chen, TianShu Zeng, JiaoYue Zhang, Jie Min, ShengHua Tian, Hao Zhang, Hantao Huang, Ping Wang, Xiang Hu, LuLu Chen

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 12 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 12 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 2 17%
Lecturer 1 8%
Unknown 9 75%
Readers by discipline Count As %
Pharmacology, Toxicology and Pharmaceutical Science 1 8%
Computer Science 1 8%
Unknown 10 83%
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 28 November 2022.
All research outputs
#22,778,604
of 25,392,582 outputs
Outputs from Frontiers in endocrinology
#8,341
of 13,030 outputs
Outputs of similar age
#415,600
of 487,037 outputs
Outputs of similar age from Frontiers in endocrinology
#528
of 951 outputs
Altmetric has tracked 25,392,582 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 13,030 research outputs from this source. They receive a mean Attention Score of 4.9. 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 487,037 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 951 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.