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HiRAND: A novel GCN semi-supervised deep learning-based framework for classification and feature selection in drug research and development

Overview of attention for article published in Frontiers in oncology, January 2023
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (51st percentile)
  • Good Attention Score compared to outputs of the same age and source (77th percentile)

Mentioned by

twitter
4 X users

Readers on

mendeley
2 Mendeley
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Title
HiRAND: A novel GCN semi-supervised deep learning-based framework for classification and feature selection in drug research and development
Published in
Frontiers in oncology, January 2023
DOI 10.3389/fonc.2023.1047556
Pubmed ID
Authors

Yue Huang, Zhiwei Rong, Liuchao Zhang, Zhenyi Xu, Jianxin Ji, Jia He, Weisha Liu, Yan Hou, Kang Li

X Demographics

X Demographics

The data shown below were collected from the profiles of 4 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 2 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 2 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 1 50%
Researcher 1 50%
Readers by discipline Count As %
Engineering 2 100%
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 14 February 2023.
All research outputs
#15,754,982
of 25,392,582 outputs
Outputs from Frontiers in oncology
#4,979
of 22,436 outputs
Outputs of similar age
#221,976
of 472,368 outputs
Outputs of similar age from Frontiers in oncology
#268
of 1,393 outputs
Altmetric has tracked 25,392,582 research outputs across all sources so far. This one is in the 37th percentile – i.e., 37% 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 75% 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 472,368 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 51% of its contemporaries.
We're also able to compare this research output to 1,393 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 77% of its contemporaries.