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The application of a neural network to predict hypotension and vasopressor requirements non-invasively in obstetric patients having spinal anesthesia for elective cesarean section (C/S)

Overview of attention for article published in BMC Anesthesiology, May 2020
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (55th percentile)
  • High Attention Score compared to outputs of the same age and source (82nd percentile)

Mentioned by

patent
3 patents

Citations

dimensions_citation
7 Dimensions

Readers on

mendeley
50 Mendeley
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Title
The application of a neural network to predict hypotension and vasopressor requirements non-invasively in obstetric patients having spinal anesthesia for elective cesarean section (C/S)
Published in
BMC Anesthesiology, May 2020
DOI 10.1186/s12871-020-01015-9
Pubmed ID
Authors

Irwin Gratz, Martin Baruch, Magdy Takla, Julia Seaman, Isabel Allen, Brian McEniry, Edward Deal

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 50 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 50 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 9 18%
Student > Ph. D. Student 4 8%
Student > Master 4 8%
Student > Doctoral Student 3 6%
Other 3 6%
Other 8 16%
Unknown 19 38%
Readers by discipline Count As %
Medicine and Dentistry 11 22%
Nursing and Health Professions 5 10%
Agricultural and Biological Sciences 3 6%
Engineering 3 6%
Pharmacology, Toxicology and Pharmaceutical Science 2 4%
Other 5 10%
Unknown 21 42%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 04 August 2022.
All research outputs
#7,544,407
of 23,016,919 outputs
Outputs from BMC Anesthesiology
#319
of 1,509 outputs
Outputs of similar age
#153,582
of 378,090 outputs
Outputs of similar age from BMC Anesthesiology
#8
of 52 outputs
Altmetric has tracked 23,016,919 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,509 research outputs from this source. They receive a mean Attention Score of 3.1. This one has done well, scoring higher than 77% 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 378,090 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 55% of its contemporaries.
We're also able to compare this research output to 52 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 82% of its contemporaries.