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Deep learning predicts immune checkpoint inhibitor-related pneumonitis from pretreatment computed tomography images

Overview of attention for article published in Frontiers in Physiology, July 2022
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  • Average Attention Score compared to outputs of the same age
  • Above-average Attention Score compared to outputs of the same age and source (52nd percentile)

Mentioned by

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3 X users

Citations

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5 Dimensions

Readers on

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19 Mendeley
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Title
Deep learning predicts immune checkpoint inhibitor-related pneumonitis from pretreatment computed tomography images
Published in
Frontiers in Physiology, July 2022
DOI 10.3389/fphys.2022.978222
Pubmed ID
Authors

Peixin Tan, Wei Huang, Lingling Wang, Guanhua Deng, Ye Yuan, Shili Qiu, Dong Ni, Shasha Du, Jun Cheng

Timeline

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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 19 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 19 100%

Demographic breakdown

Readers by professional status Count As %
Student > Doctoral Student 2 11%
Student > Bachelor 1 5%
Student > Ph. D. Student 1 5%
Student > Master 1 5%
Researcher 1 5%
Other 1 5%
Unknown 12 63%
Readers by discipline Count As %
Pharmacology, Toxicology and Pharmaceutical Science 1 5%
Mathematics 1 5%
Computer Science 1 5%
Immunology and Microbiology 1 5%
Sports and Recreations 1 5%
Other 2 11%
Unknown 12 63%
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 06 September 2022.
All research outputs
#16,581,265
of 24,394,820 outputs
Outputs from Frontiers in Physiology
#7,331
of 14,988 outputs
Outputs of similar age
#244,430
of 421,654 outputs
Outputs of similar age from Frontiers in Physiology
#323
of 714 outputs
Altmetric has tracked 24,394,820 research outputs across all sources so far. This one is in the 21st percentile – i.e., 21% of other outputs scored the same or lower than it.
So far Altmetric has tracked 14,988 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.8. This one is in the 47th percentile – i.e., 47% 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 421,654 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 30th percentile – i.e., 30% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 714 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 52% of its contemporaries.