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Glycemic and lipid variability for predicting complications and mortality in diabetes mellitus using machine learning

Overview of attention for article published in BMC Endocrine Disorders, May 2021
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About this Attention Score

  • Average Attention Score compared to outputs of the same age

Mentioned by

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3 X users

Citations

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64 Dimensions

Readers on

mendeley
99 Mendeley
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Title
Glycemic and lipid variability for predicting complications and mortality in diabetes mellitus using machine learning
Published in
BMC Endocrine Disorders, May 2021
DOI 10.1186/s12902-021-00751-4
Pubmed ID
Authors

Sharen Lee, Jiandong Zhou, Wing Tak Wong, Tong Liu, William K. K. Wu, Ian Chi Kei Wong, Qingpeng Zhang, Gary Tse

X Demographics

X Demographics

The data shown below were collected from the profiles of 3 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 99 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 99 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 13 13%
Student > Bachelor 10 10%
Researcher 6 6%
Student > Ph. D. Student 5 5%
Lecturer 4 4%
Other 10 10%
Unknown 51 52%
Readers by discipline Count As %
Medicine and Dentistry 18 18%
Computer Science 10 10%
Nursing and Health Professions 6 6%
Engineering 5 5%
Pharmacology, Toxicology and Pharmaceutical Science 2 2%
Other 5 5%
Unknown 53 54%
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 14 May 2021.
All research outputs
#15,871,137
of 23,576,969 outputs
Outputs from BMC Endocrine Disorders
#435
of 799 outputs
Outputs of similar age
#261,248
of 440,680 outputs
Outputs of similar age from BMC Endocrine Disorders
#26
of 39 outputs
Altmetric has tracked 23,576,969 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 799 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.2. This one is in the 34th percentile – i.e., 34% 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 440,680 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 30th percentile – i.e., 30% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 39 others from the same source and published within six weeks on either side of this one. This one is in the 25th percentile – i.e., 25% of its contemporaries scored the same or lower than it.