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Prediction model of obstructive sleep apnea–related hypertension: Machine learning–based development and interpretation study

Overview of attention for article published in Frontiers in Cardiovascular Medicine, December 2022
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Mentioned by

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2 X users

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mendeley
26 Mendeley
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Title
Prediction model of obstructive sleep apnea–related hypertension: Machine learning–based development and interpretation study
Published in
Frontiers in Cardiovascular Medicine, December 2022
DOI 10.3389/fcvm.2022.1042996
Pubmed ID
Authors

Yewen Shi, Lina Ma, Xi Chen, Wenle Li, Yani Feng, Yitong Zhang, Zine Cao, Yuqi Yuan, Yushan Xie, Haiqin Liu, Libo Yin, Changying Zhao, Shinan Wu, Xiaoyong Ren

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

Geographical breakdown

Country Count As %
Unknown 26 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 4 15%
Student > Bachelor 2 8%
Researcher 2 8%
Student > Ph. D. Student 2 8%
Professor 1 4%
Other 3 12%
Unknown 12 46%
Readers by discipline Count As %
Computer Science 3 12%
Psychology 2 8%
Nursing and Health Professions 2 8%
Environmental Science 1 4%
Business, Management and Accounting 1 4%
Other 3 12%
Unknown 14 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 06 December 2022.
All research outputs
#18,789,320
of 23,283,373 outputs
Outputs from Frontiers in Cardiovascular Medicine
#3,360
of 7,182 outputs
Outputs of similar age
#299,760
of 437,971 outputs
Outputs of similar age from Frontiers in Cardiovascular Medicine
#317
of 809 outputs
Altmetric has tracked 23,283,373 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,182 research outputs from this source. They receive a mean Attention Score of 4.3. This one is in the 38th percentile – i.e., 38% 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 437,971 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 21st percentile – i.e., 21% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 809 others from the same source and published within six weeks on either side of this one. This one is in the 42nd percentile – i.e., 42% of its contemporaries scored the same or lower than it.