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Pixel-level multimodal fusion deep networks for predicting subcellular organelle localization from label-free live-cell imaging

Overview of attention for article published in Frontiers in Genetics, October 2022
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Mentioned by

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2 X users

Citations

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3 Dimensions

Readers on

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7 Mendeley
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Title
Pixel-level multimodal fusion deep networks for predicting subcellular organelle localization from label-free live-cell imaging
Published in
Frontiers in Genetics, October 2022
DOI 10.3389/fgene.2022.1002327
Pubmed ID
Authors

Zhihao Wei, Xi Liu, Ruiqing Yan, Guocheng Sun, Weiyong Yu, Qiang Liu, Qianjin Guo

X Demographics

X Demographics

The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
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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 > Ph. D. Student 1 14%
Student > Bachelor 1 14%
Unknown 5 71%
Readers by discipline Count As %
Computer Science 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 17 November 2022.
All research outputs
#19,187,140
of 23,776,941 outputs
Outputs from Frontiers in Genetics
#7,451
of 12,688 outputs
Outputs of similar age
#311,170
of 447,257 outputs
Outputs of similar age from Frontiers in Genetics
#450
of 1,011 outputs
Altmetric has tracked 23,776,941 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 12,688 research outputs from this source. They receive a mean Attention Score of 3.7. This one is in the 28th percentile – i.e., 28% 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 447,257 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 19th percentile – i.e., 19% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 1,011 others from the same source and published within six weeks on either side of this one. This one is in the 40th percentile – i.e., 40% of its contemporaries scored the same or lower than it.