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Performance evaluation of an AI-based preoperative planning software application for automatic selection of pedicle screws based on computed tomography images

Overview of attention for article published in Frontiers in Surgery, September 2023
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Mentioned by

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1 X user

Citations

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2 Dimensions

Readers on

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10 Mendeley
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Title
Performance evaluation of an AI-based preoperative planning software application for automatic selection of pedicle screws based on computed tomography images
Published in
Frontiers in Surgery, September 2023
DOI 10.3389/fsurg.2023.1247527
Pubmed ID
Authors

Shanhang Jia, Yuanzhi Weng, Kai Wang, Huan Qi, Yuhua Yang, Chi Ma, Weijia William Lu, Hao Wu

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

Geographical breakdown

Country Count As %
Unknown 10 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 2 20%
Student > Ph. D. Student 1 10%
Researcher 1 10%
Unknown 6 60%
Readers by discipline Count As %
Nursing and Health Professions 1 10%
Computer Science 1 10%
Medicine and Dentistry 1 10%
Engineering 1 10%
Unknown 6 60%
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 11 September 2023.
All research outputs
#22,834,710
of 25,460,914 outputs
Outputs from Frontiers in Surgery
#2,291
of 3,977 outputs
Outputs of similar age
#291,665
of 352,066 outputs
Outputs of similar age from Frontiers in Surgery
#66
of 108 outputs
Altmetric has tracked 25,460,914 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 3,977 research outputs from this source. They receive a mean Attention Score of 2.2. 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 352,066 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 108 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.