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Attention Score in Context
| Title |
Comparative assessment of established and deep learning‐based segmentation methods for hippocampal volume estimation in brain magnetic resonance imaging analysis
|
|---|---|
| Published in |
NMR in Biomedicine, May 2024
|
| DOI | 10.1002/nbm.5169 |
| Pubmed ID | |
| Authors |
Hsi‐Chun Wang, Chia‐Sho Chen, Chung‐Chin Kuo, Teng‐Yi Huang, Kuei‐Hong Kuo, Tzu‐Chao Chuang, Yi‐Ru Lin, Hsiao‐Wen Chung, for the Alzheimer's Disease Neuroimaging Initiative |
Attention Score in Context
This research output has an Altmetric Attention Score of 7. 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 10 May 2024.
All research outputs
#4,966,503
of 25,882,826 outputs
Outputs from NMR in Biomedicine
#176
of 1,969 outputs
Outputs of similar age
#30,385
of 157,792 outputs
Outputs of similar age from NMR in Biomedicine
#2
of 9 outputs
Altmetric has tracked 25,882,826 research outputs across all sources so far. Compared to these this one has done well and is in the 79th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,969 research outputs from this source. They receive a mean Attention Score of 3.4. This one has done particularly well, scoring higher than 90% 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 157,792 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 79% of its contemporaries.
We're also able to compare this research output to 9 others from the same source and published within six weeks on either side of this one. This one has scored higher than 7 of them.