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Development of a deep learning model for early gastric cancer diagnosis using preoperative computed tomography images

Overview of attention for article published in Frontiers in oncology, October 2023
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1 X user

Readers on

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8 Mendeley
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Title
Development of a deep learning model for early gastric cancer diagnosis using preoperative computed tomography images
Published in
Frontiers in oncology, October 2023
DOI 10.3389/fonc.2023.1265366
Pubmed ID
Authors

Zhihong Gao, Zhuo Yu, Xiang Zhang, Chun Chen, Zhifang Pan, Xiaodong Chen, Weihong Lin, Jun Chen, Qichuan Zhuge, Xian Shen

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

Geographical breakdown

Country Count As %
Unknown 8 100%

Demographic breakdown

Readers by professional status Count As %
Unspecified 3 38%
Lecturer 1 13%
Unknown 4 50%
Readers by discipline Count As %
Unspecified 3 38%
Environmental Science 1 13%
Unknown 4 50%
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 10 October 2023.
All research outputs
#22,778,604
of 25,394,764 outputs
Outputs from Frontiers in oncology
#15,927
of 22,440 outputs
Outputs of similar age
#293,205
of 355,644 outputs
Outputs of similar age from Frontiers in oncology
#815
of 932 outputs
Altmetric has tracked 25,394,764 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 22,440 research outputs from this source. They receive a mean Attention Score of 3.0. 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 355,644 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 932 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.