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Machine learning in predicting T-score in the Oxford classification system of IgA nephropathy

Overview of attention for article published in Frontiers in immunology, August 2023
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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 (58th percentile)

Mentioned by

twitter
3 X users

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mendeley
4 Mendeley
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Title
Machine learning in predicting T-score in the Oxford classification system of IgA nephropathy
Published in
Frontiers in immunology, August 2023
DOI 10.3389/fimmu.2023.1224631
Pubmed ID
Authors

Lin-Lin Xu, Di Zhang, Hao-Yi Weng, Li-Zhong Wang, Ruo-Yan Chen, Gang Chen, Su-Fang Shi, Li-Jun Liu, Xu-Hui Zhong, Shen-Da Hong, Li-Xin Duan, Ji-Cheng Lv, Xu-Jie Zhou, Hong Zhang

X Demographics

X Demographics

The data shown below were collected from the profiles of 3 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 4 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 4 100%

Demographic breakdown

Readers by professional status Count As %
Lecturer 1 25%
Unknown 3 75%
Readers by discipline Count As %
Medicine and Dentistry 1 25%
Unknown 3 75%
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 06 August 2023.
All research outputs
#16,323,211
of 25,872,466 outputs
Outputs from Frontiers in immunology
#16,843
of 32,522 outputs
Outputs of similar age
#177,194
of 363,433 outputs
Outputs of similar age from Frontiers in immunology
#498
of 1,206 outputs
Altmetric has tracked 25,872,466 research outputs across all sources so far. This one is in the 36th percentile – i.e., 36% of other outputs scored the same or lower than it.
So far Altmetric has tracked 32,522 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.5. This one is in the 47th percentile – i.e., 47% 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 363,433 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 50% of its contemporaries.
We're also able to compare this research output to 1,206 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 58% of its contemporaries.