↓ Skip to main content

Automated prediction of early spontaneous miscarriage based on the analyzing ultrasonographic gestational sac imaging by the convolutional neural network: a case-control and cohort study

Overview of attention for article published in BMC Pregnancy and Childbirth, August 2022
Altmetric Badge

About this Attention Score

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

Mentioned by

twitter
1 X user

Citations

dimensions_citation
6 Dimensions

Readers on

mendeley
33 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
Automated prediction of early spontaneous miscarriage based on the analyzing ultrasonographic gestational sac imaging by the convolutional neural network: a case-control and cohort study
Published in
BMC Pregnancy and Childbirth, August 2022
DOI 10.1186/s12884-022-04936-0
Pubmed ID
Authors

Yu Wang, Qixin Zhang, Chenghuan Yin, Lizhu Chen, Zeyu Yang, Shanshan Jia, Xue Sun, Yuzuo Bai, Fangfang Han, Zhengwei Yuan

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

Geographical breakdown

Country Count As %
Unknown 33 100%

Demographic breakdown

Readers by professional status Count As %
Unspecified 16 48%
Student > Doctoral Student 2 6%
Student > Bachelor 1 3%
Student > Ph. D. Student 1 3%
Researcher 1 3%
Other 1 3%
Unknown 11 33%
Readers by discipline Count As %
Unspecified 16 48%
Medicine and Dentistry 3 9%
Nursing and Health Professions 1 3%
Psychology 1 3%
Computer Science 1 3%
Other 0 0%
Unknown 11 33%
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
#17,619,915
of 25,830,005 outputs
Outputs from BMC Pregnancy and Childbirth
#3,431
of 4,883 outputs
Outputs of similar age
#254,883
of 434,329 outputs
Outputs of similar age from BMC Pregnancy and Childbirth
#74
of 136 outputs
Altmetric has tracked 25,830,005 research outputs across all sources so far. This one is in the 21st percentile – i.e., 21% of other outputs scored the same or lower than it.
So far Altmetric has tracked 4,883 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 9.2. This one is in the 21st percentile – i.e., 21% 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 434,329 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 30th percentile – i.e., 30% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 136 others from the same source and published within six weeks on either side of this one. This one is in the 34th percentile – i.e., 34% of its contemporaries scored the same or lower than it.