↓ Skip to main content

Enhancing classification of preterm-term birth using continuous wavelet transform and entropy-based methods of electrohysterogram signals

Overview of attention for article published in Frontiers in endocrinology, January 2023
Altmetric Badge

About this Attention Score

  • Average Attention Score compared to outputs of the same age
  • Above-average Attention Score compared to outputs of the same age and source (64th percentile)

Mentioned by

twitter
2 X users

Citations

dimensions_citation
7 Dimensions

Readers on

mendeley
15 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
Enhancing classification of preterm-term birth using continuous wavelet transform and entropy-based methods of electrohysterogram signals
Published in
Frontiers in endocrinology, January 2023
DOI 10.3389/fendo.2022.1035615
Pubmed ID
Authors

Héctor Romero-Morales, Jenny Noemí Muñoz-Montes de, Rodrigo Mora-Martínez, Yecid Mina-Paz, José Javier Reyes-Lagos

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.
As of 1 July 2024, you may notice a temporary increase in the numbers of X profiles with Unknown location. Click here to learn more.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 15 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 15 100%

Demographic breakdown

Readers by professional status Count As %
Lecturer 1 7%
Student > Bachelor 1 7%
Professor 1 7%
Student > Ph. D. Student 1 7%
Student > Master 1 7%
Other 1 7%
Unknown 9 60%
Readers by discipline Count As %
Nursing and Health Professions 2 13%
Engineering 2 13%
Medicine and Dentistry 1 7%
Environmental Science 1 7%
Unknown 9 60%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 January 2023.
All research outputs
#17,306,361
of 26,181,776 outputs
Outputs from Frontiers in endocrinology
#4,610
of 13,380 outputs
Outputs of similar age
#263,302
of 487,343 outputs
Outputs of similar age from Frontiers in endocrinology
#289
of 1,005 outputs
Altmetric has tracked 26,181,776 research outputs across all sources so far. This one is in the 31st percentile – i.e., 31% of other outputs scored the same or lower than it.
So far Altmetric has tracked 13,380 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.2. This one has gotten more attention than average, scoring higher than 59% of its peers.
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 487,343 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 42nd percentile – i.e., 42% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 1,005 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 64% of its contemporaries.