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Identification of a small mutation panel of coding sequences to predict the efficacy of immunotherapy for lung adenocarcinoma

Overview of attention for article published in Journal of Translational Medicine, January 2020
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (83rd percentile)
  • High Attention Score compared to outputs of the same age and source (84th percentile)

Mentioned by

news
1 news outlet
twitter
1 X user

Citations

dimensions_citation
5 Dimensions

Readers on

mendeley
17 Mendeley
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Title
Identification of a small mutation panel of coding sequences to predict the efficacy of immunotherapy for lung adenocarcinoma
Published in
Journal of Translational Medicine, January 2020
DOI 10.1186/s12967-019-02199-6
Pubmed ID
Authors

Ying Li, Wenbin Jiang, Tianhao Li, Mengyue Li, Xin Li, Zheyang Zhang, Sainan Zhang, Yixin Liu, Wenyuan Zhao, Yunyan Gu, Lishuang Qi, Lu Ao, Zheng Guo

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.
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 %
Researcher 3 18%
Student > Master 2 12%
Other 1 6%
Student > Doctoral Student 1 6%
Student > Ph. D. Student 1 6%
Other 2 12%
Unknown 7 41%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 3 18%
Medicine and Dentistry 2 12%
Agricultural and Biological Sciences 1 6%
Pharmacology, Toxicology and Pharmaceutical Science 1 6%
Immunology and Microbiology 1 6%
Other 1 6%
Unknown 8 47%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 10. 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 24 May 2023.
All research outputs
#3,228,193
of 23,818,521 outputs
Outputs from Journal of Translational Medicine
#531
of 4,221 outputs
Outputs of similar age
#77,350
of 460,497 outputs
Outputs of similar age from Journal of Translational Medicine
#14
of 83 outputs
Altmetric has tracked 23,818,521 research outputs across all sources so far. Compared to these this one has done well and is in the 86th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,221 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.7. This one has done well, scoring higher than 87% 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 460,497 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 83% of its contemporaries.
We're also able to compare this research output to 83 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 84% of its contemporaries.