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Prediction of acute appendicitis among patients with undifferentiated abdominal pain at emergency department

Overview of attention for article published in BMC Medical Research Methodology, January 2022
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  • Average Attention Score compared to outputs of the same age
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

twitter
2 X users

Citations

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8 Dimensions

Readers on

mendeley
35 Mendeley
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Title
Prediction of acute appendicitis among patients with undifferentiated abdominal pain at emergency department
Published in
BMC Medical Research Methodology, January 2022
DOI 10.1186/s12874-021-01490-9
Pubmed ID
Authors

Dai Su, Qinmengge Li, Tao Zhang, Philip Veliz, Yingchun Chen, Kevin He, Prashant Mahajan, Xingyu Zhang

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.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 35 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 35 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 4 11%
Student > Doctoral Student 3 9%
Student > Ph. D. Student 2 6%
Librarian 1 3%
Unspecified 1 3%
Other 2 6%
Unknown 22 63%
Readers by discipline Count As %
Medicine and Dentistry 5 14%
Computer Science 3 9%
Nursing and Health Professions 2 6%
Business, Management and Accounting 1 3%
Sports and Recreations 1 3%
Other 3 9%
Unknown 20 57%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 24 November 2022.
All research outputs
#15,063,168
of 23,179,757 outputs
Outputs from BMC Medical Research Methodology
#1,470
of 2,045 outputs
Outputs of similar age
#264,878
of 509,929 outputs
Outputs of similar age from BMC Medical Research Methodology
#33
of 51 outputs
Altmetric has tracked 23,179,757 research outputs across all sources so far. This one is in the 32nd percentile – i.e., 32% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2,045 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.3. This one is in the 25th percentile – i.e., 25% 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 509,929 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 44th percentile – i.e., 44% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 51 others from the same source and published within six weeks on either side of this one. This one is in the 33rd percentile – i.e., 33% of its contemporaries scored the same or lower than it.