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Machine learning-based predictor for neurologic outcomes in patients undergoing extracorporeal cardiopulmonary resuscitation

Overview of attention for article published in Frontiers in Cardiovascular Medicine, November 2023
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2 X users

Citations

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Title
Machine learning-based predictor for neurologic outcomes in patients undergoing extracorporeal cardiopulmonary resuscitation
Published in
Frontiers in Cardiovascular Medicine, November 2023
DOI 10.3389/fcvm.2023.1278374
Pubmed ID
Authors

Tae Wan Kim, Joonghyun Ahn, Jeong-Am Ryu

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

Geographical breakdown

Country Count As %
Unknown 6 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 1 17%
Unknown 5 83%
Readers by discipline Count As %
Nursing and Health Professions 1 17%
Unknown 5 83%
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 18 November 2023.
All research outputs
#20,200,688
of 24,834,604 outputs
Outputs from Frontiers in Cardiovascular Medicine
#4,191
of 8,726 outputs
Outputs of similar age
#109,137
of 162,928 outputs
Outputs of similar age from Frontiers in Cardiovascular Medicine
#83
of 237 outputs
Altmetric has tracked 24,834,604 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 8,726 research outputs from this source. They receive a mean Attention Score of 4.3. This one is in the 38th percentile – i.e., 38% 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 162,928 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 21st percentile – i.e., 21% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 237 others from the same source and published within six weeks on either side of this one. This one is in the 18th percentile – i.e., 18% of its contemporaries scored the same or lower than it.