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Automated detection of MRI-negative temporal lobe epilepsy with ROI-based morphometric features and machine learning

Overview of attention for article published in Frontiers in Neurology, January 2024
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (63rd percentile)
  • High Attention Score compared to outputs of the same age and source (82nd percentile)

Mentioned by

twitter
5 X users

Readers on

mendeley
5 Mendeley
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Title
Automated detection of MRI-negative temporal lobe epilepsy with ROI-based morphometric features and machine learning
Published in
Frontiers in Neurology, January 2024
DOI 10.3389/fneur.2024.1323623
Pubmed ID
Authors

Lin Yang, Bo Peng, Wei Gao, Rixi A, Yan Liu, Jiawei Liang, Mo Zhu, Haiyang Hu, Zuhong Lu, Chunying Pang, Yakang Dai, Yu Sun

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.
As of 1 July 2024, you may notice a temporary increase in the numbers of X profiles with Unknown location. Click here to learn more.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 5 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 5 100%

Demographic breakdown

Readers by professional status Count As %
Unspecified 2 40%
Student > Ph. D. Student 1 20%
Student > Bachelor 1 20%
Unknown 1 20%
Readers by discipline Count As %
Unspecified 1 20%
Agricultural and Biological Sciences 1 20%
Computer Science 1 20%
Medicine and Dentistry 1 20%
Unknown 1 20%
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 01 February 2024.
All research outputs
#14,933,374
of 26,397,269 outputs
Outputs from Frontiers in Neurology
#5,536
of 15,015 outputs
Outputs of similar age
#136,662
of 379,703 outputs
Outputs of similar age from Frontiers in Neurology
#94
of 562 outputs
Altmetric has tracked 26,397,269 research outputs across all sources so far. This one is in the 43rd percentile – i.e., 43% of other outputs scored the same or lower than it.
So far Altmetric has tracked 15,015 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.6. This one has gotten more attention than average, scoring higher than 62% 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 379,703 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 63% of its contemporaries.
We're also able to compare this research output to 562 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.