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Deep learning in CT image segmentation of cervical cancer: a systematic review and meta-analysis

Overview of attention for article published in Radiation Oncology, November 2022
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  • Average Attention Score compared to outputs of the same age and source

Mentioned by

twitter
3 X users

Citations

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11 Dimensions

Readers on

mendeley
41 Mendeley
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Title
Deep learning in CT image segmentation of cervical cancer: a systematic review and meta-analysis
Published in
Radiation Oncology, November 2022
DOI 10.1186/s13014-022-02148-6
Pubmed ID
Authors

Chongze Yang, Lan-hui Qin, Yu-en Xie, Jin-yuan Liao

X Demographics

X Demographics

The data shown below were collected from the profiles of 3 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 41 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 41 100%

Demographic breakdown

Readers by professional status Count As %
Unspecified 6 15%
Researcher 3 7%
Student > Ph. D. Student 3 7%
Student > Bachelor 2 5%
Lecturer 2 5%
Other 7 17%
Unknown 18 44%
Readers by discipline Count As %
Unspecified 6 15%
Medicine and Dentistry 4 10%
Nursing and Health Professions 2 5%
Computer Science 2 5%
Physics and Astronomy 2 5%
Other 7 17%
Unknown 18 44%
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 14 November 2022.
All research outputs
#18,733,166
of 23,885,338 outputs
Outputs from Radiation Oncology
#1,299
of 2,067 outputs
Outputs of similar age
#294,687
of 430,378 outputs
Outputs of similar age from Radiation Oncology
#16
of 28 outputs
Altmetric has tracked 23,885,338 research outputs across all sources so far. This one is in the 18th percentile – i.e., 18% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2,067 research outputs from this source. They receive a mean Attention Score of 2.9. This one is in the 30th percentile – i.e., 30% 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 430,378 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 27th percentile – i.e., 27% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 28 others from the same source and published within six weeks on either side of this one. This one is in the 42nd percentile – i.e., 42% of its contemporaries scored the same or lower than it.