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Artificial intelligence improves the accuracy of residents in the diagnosis of hip fractures: a multicenter study

Overview of attention for article published in BMC Musculoskeletal Disorders, May 2021
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Mentioned by

twitter
2 tweeters

Citations

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4 Dimensions

Readers on

mendeley
37 Mendeley
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Title
Artificial intelligence improves the accuracy of residents in the diagnosis of hip fractures: a multicenter study
Published in
BMC Musculoskeletal Disorders, May 2021
DOI 10.1186/s12891-021-04260-2
Authors

Yoichi Sato, Yasuhiko Takegami, Takamune Asamoto, Yutaro Ono, Tsugeno Hidetoshi, Ryosuke Goto, Akira Kitamura, Seiwa Honda

Twitter Demographics

The data shown below were collected from the profiles of 2 tweeters 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 37 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 37 100%

Demographic breakdown

Readers by professional status Count As %
Student > Doctoral Student 6 16%
Researcher 4 11%
Student > Ph. D. Student 4 11%
Student > Postgraduate 3 8%
Student > Bachelor 2 5%
Other 3 8%
Unknown 15 41%
Readers by discipline Count As %
Medicine and Dentistry 9 24%
Computer Science 4 11%
Engineering 3 8%
Business, Management and Accounting 1 3%
Psychology 1 3%
Other 5 14%
Unknown 14 38%

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 04 May 2021.
All research outputs
#16,976,523
of 21,044,876 outputs
Outputs from BMC Musculoskeletal Disorders
#2,870
of 3,715 outputs
Outputs of similar age
#247,131
of 339,114 outputs
Outputs of similar age from BMC Musculoskeletal Disorders
#1
of 1 outputs
Altmetric has tracked 21,044,876 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 3,715 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.9. This one is in the 10th percentile – i.e., 10% 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 339,114 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 17th percentile – i.e., 17% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them