↓ Skip to main content

A deep learning-based automatic staging method for early endometrial cancer on MRI images

Overview of attention for article published in Frontiers in Physiology, August 2022
Altmetric Badge

About this Attention Score

  • Average Attention Score compared to outputs of the same age and source

Mentioned by

twitter
2 X users

Readers on

mendeley
24 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
A deep learning-based automatic staging method for early endometrial cancer on MRI images
Published in
Frontiers in Physiology, August 2022
DOI 10.3389/fphys.2022.974245
Pubmed ID
Authors

Wei Mao, Chunxia Chen, Huachao Gao, Liu Xiong, Yongping Lin

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

Geographical breakdown

Country Count As %
Unknown 24 100%

Demographic breakdown

Readers by professional status Count As %
Unspecified 2 8%
Student > Bachelor 2 8%
Student > Doctoral Student 1 4%
Student > Ph. D. Student 1 4%
Researcher 1 4%
Other 2 8%
Unknown 15 63%
Readers by discipline Count As %
Medicine and Dentistry 3 13%
Unspecified 2 8%
Agricultural and Biological Sciences 2 8%
Biochemistry, Genetics and Molecular Biology 1 4%
Nursing and Health Professions 1 4%
Other 2 8%
Unknown 13 54%
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 16 September 2022.
All research outputs
#19,897,240
of 24,452,844 outputs
Outputs from Frontiers in Physiology
#8,924
of 15,036 outputs
Outputs of similar age
#308,559
of 420,248 outputs
Outputs of similar age from Frontiers in Physiology
#421
of 779 outputs
Altmetric has tracked 24,452,844 research outputs across all sources so far. This one is in the 10th percentile – i.e., 10% of other outputs scored the same or lower than it.
So far Altmetric has tracked 15,036 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.8. This one is in the 32nd percentile – i.e., 32% 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 420,248 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 15th percentile – i.e., 15% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 779 others from the same source and published within six weeks on either side of this one. This one is in the 35th percentile – i.e., 35% of its contemporaries scored the same or lower than it.