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Integrating machine learning to construct aberrant alternative splicing event related classifiers to predict prognosis and immunotherapy response in patients with hepatocellular carcinoma

Overview of attention for article published in Frontiers in Pharmacology, October 2022
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age and source (59th percentile)

Mentioned by

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3 X users

Citations

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1 Dimensions

Readers on

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7 Mendeley
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Title
Integrating machine learning to construct aberrant alternative splicing event related classifiers to predict prognosis and immunotherapy response in patients with hepatocellular carcinoma
Published in
Frontiers in Pharmacology, October 2022
DOI 10.3389/fphar.2022.1019988
Pubmed ID
Authors

Wangrui Liu, Shuai Zhao, Wenhao Xu, Jianfeng Xiang, Chuanyu Li, Jun Li, Han Ding, Hailiang Zhang, Yichi Zhang, Haineng Huang, Jian Wang, Tao Wang, Bo Zhai, Lei Pan

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.
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 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 %
Researcher 1 14%
Student > Master 1 14%
Unknown 5 71%
Readers by discipline Count As %
Pharmacology, Toxicology and Pharmaceutical Science 1 14%
Engineering 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 20 October 2022.
All research outputs
#18,733,166
of 23,885,338 outputs
Outputs from Frontiers in Pharmacology
#7,656
of 17,745 outputs
Outputs of similar age
#291,331
of 426,767 outputs
Outputs of similar age from Frontiers in Pharmacology
#532
of 1,515 outputs
Altmetric has tracked 23,885,338 research outputs across all sources so far. This one is in the 18th percentile – i.e., 18% of other outputs scored the same or lower than it.
So far Altmetric has tracked 17,745 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.1. This one is in the 49th percentile – i.e., 49% 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 426,767 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 27th percentile – i.e., 27% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 1,515 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 59% of its contemporaries.