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Identifying diagnostic markers and constructing a prognostic model for small-cell lung cancer based on blood exosome-related genes and machine-learning methods

Overview of attention for article published in Frontiers in oncology, December 2022
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1 X user

Citations

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Readers on

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17 Mendeley
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Title
Identifying diagnostic markers and constructing a prognostic model for small-cell lung cancer based on blood exosome-related genes and machine-learning methods
Published in
Frontiers in oncology, December 2022
DOI 10.3389/fonc.2022.1077118
Pubmed ID
Authors

Kun Zhang, Chaoguo Zhang, Ke Wang, Xiuli Teng, Mingwei Chen

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user 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 17 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 17 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 8 47%
Researcher 1 6%
Lecturer 1 6%
Student > Doctoral Student 1 6%
Unknown 6 35%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 8 47%
Nursing and Health Professions 1 6%
Computer Science 1 6%
Unknown 7 41%
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 09 January 2023.
All research outputs
#23,501,977
of 26,180,771 outputs
Outputs from Frontiers in oncology
#16,383
of 22,919 outputs
Outputs of similar age
#420,588
of 490,017 outputs
Outputs of similar age from Frontiers in oncology
#1,395
of 1,495 outputs
Altmetric has tracked 26,180,771 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 22,919 research outputs from this source. They receive a mean Attention Score of 3.1. This one is in the 1st percentile – i.e., 1% 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 490,017 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 1,495 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.