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The development of machine learning in bariatric surgery

Overview of attention for article published in Frontiers in Surgery, February 2023
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Mentioned by

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1 X user

Citations

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2 Dimensions

Readers on

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7 Mendeley
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Title
The development of machine learning in bariatric surgery
Published in
Frontiers in Surgery, February 2023
DOI 10.3389/fsurg.2023.1102711
Pubmed ID
Authors

Bassey Enodien, Stephanie Taha-Mehlitz, Baraa Saad, Maya Nasser, Daniel M. Frey, Anas Taha

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

Geographical breakdown

Country Count As %
Unknown 7 100%

Demographic breakdown

Readers by professional status Count As %
Student > Doctoral Student 2 29%
Student > Postgraduate 1 14%
Researcher 1 14%
Unknown 3 43%
Readers by discipline Count As %
Nursing and Health Professions 1 14%
Medicine and Dentistry 1 14%
Unknown 5 71%
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 02 April 2023.
All research outputs
#20,886,375
of 23,509,253 outputs
Outputs from Frontiers in Surgery
#1,472
of 3,273 outputs
Outputs of similar age
#302,679
of 386,333 outputs
Outputs of similar age from Frontiers in Surgery
#67
of 308 outputs
Altmetric has tracked 23,509,253 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 3,273 research outputs from this source. They receive a mean Attention Score of 2.1. This one is in the 1st percentile – i.e., 1% 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 386,333 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 308 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.