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Proteomic-Based Machine Learning Analysis Reveals PYGB as a Novel Immunohistochemical Biomarker to Distinguish Inverted Urothelial Papilloma From Low-Grade Papillary Urothelial Carcinoma With…

Overview of attention for article published in Frontiers in oncology, March 2022
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (53rd percentile)
  • High Attention Score compared to outputs of the same age and source (81st percentile)

Mentioned by

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5 X users

Citations

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3 Dimensions

Readers on

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3 Mendeley
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Title
Proteomic-Based Machine Learning Analysis Reveals PYGB as a Novel Immunohistochemical Biomarker to Distinguish Inverted Urothelial Papilloma From Low-Grade Papillary Urothelial Carcinoma With Inverted Growth
Published in
Frontiers in oncology, March 2022
DOI 10.3389/fonc.2022.841398
Pubmed ID
Authors

Minsun Jung, Cheol Lee, Dohyun Han, Kwangsoo Kim, Sunah Yang, Ilias P. Nikas, Kyung Chul Moon, Hyeyoon Kim, Min Ji Song, Bohyun Kim, Hyebin Lee, Han Suk Ryu

X Demographics

X Demographics

The data shown below were collected from the profiles of 5 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 3 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 3 100%

Demographic breakdown

Readers by professional status Count As %
Unspecified 1 33%
Unknown 2 67%
Readers by discipline Count As %
Unspecified 1 33%
Unknown 2 67%
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 30 May 2022.
All research outputs
#15,106,315
of 25,392,582 outputs
Outputs from Frontiers in oncology
#4,426
of 22,436 outputs
Outputs of similar age
#206,075
of 446,344 outputs
Outputs of similar age from Frontiers in oncology
#282
of 1,525 outputs
Altmetric has tracked 25,392,582 research outputs across all sources so far. This one is in the 40th percentile – i.e., 40% of other outputs scored the same or lower than it.
So far Altmetric has tracked 22,436 research outputs from this source. They receive a mean Attention Score of 3.0. This one has done well, scoring higher than 79% 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 446,344 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 53% of its contemporaries.
We're also able to compare this research output to 1,525 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 81% of its contemporaries.