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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 tweeter

Citations

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2 Dimensions

Readers on

mendeley
3 Mendeley
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
Authors

Le Zhang, Jin Li, Kaikai Yin, Zhouyang Jiang, Tingting Li, Rong Hu, Zheng Yu, Hua Feng, Yujie Chen

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 3 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 3 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 1 33%
Researcher 1 33%
Librarian 1 33%
Readers by discipline Count As %
Unspecified 2 67%
Medicine and Dentistry 1 33%

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
#11,804,926
of 13,304,005 outputs
Outputs from BMC Bioinformatics
#4,583
of 4,991 outputs
Outputs of similar age
#210,061
of 251,017 outputs
Outputs of similar age from BMC Bioinformatics
#46
of 59 outputs
Altmetric has tracked 13,304,005 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 4,991 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 251,017 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 59 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.