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Computed tomography angiography-based analysis of high-risk intracerebral haemorrhage patients by employing a mathematical model

Overview of attention for article published in BMC Bioinformatics, May 2019
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Mentioned by

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1 X user

Citations

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24 Dimensions

Readers on

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15 Mendeley
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Title
Computed tomography angiography-based analysis of high-risk intracerebral haemorrhage patients by employing a mathematical model
Published in
BMC Bioinformatics, May 2019
DOI 10.1186/s12859-019-2741-5
Pubmed ID
Authors

Le Zhang, Jin Li, Kaikai Yin, Zhouyang Jiang, Tingting Li, Rong Hu, Zheng Yu, Hua Feng, Yujie 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 15 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 15 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 4 27%
Researcher 3 20%
Student > Ph. D. Student 2 13%
Other 1 7%
Professor 1 7%
Other 1 7%
Unknown 3 20%
Readers by discipline Count As %
Medicine and Dentistry 4 27%
Immunology and Microbiology 1 7%
Computer Science 1 7%
Social Sciences 1 7%
Engineering 1 7%
Other 0 0%
Unknown 7 47%
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 May 2019.
All research outputs
#18,679,530
of 23,144,579 outputs
Outputs from BMC Bioinformatics
#6,375
of 7,339 outputs
Outputs of similar age
#263,130
of 350,403 outputs
Outputs of similar age from BMC Bioinformatics
#161
of 189 outputs
Altmetric has tracked 23,144,579 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 7,339 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one is in the 5th percentile – i.e., 5% 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 350,403 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 14th percentile – i.e., 14% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 189 others from the same source and published within six weeks on either side of this one. This one is in the 5th percentile – i.e., 5% of its contemporaries scored the same or lower than it.