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Radiomic Feature-Based Nomogram: A Novel Technique to Predict EGFR-Activating Mutations for EGFR Tyrosin Kinase Inhibitor Therapy

Overview of attention for article published in Frontiers in oncology, August 2021
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1 X user

Citations

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9 Dimensions

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8 Mendeley
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Title
Radiomic Feature-Based Nomogram: A Novel Technique to Predict EGFR-Activating Mutations for EGFR Tyrosin Kinase Inhibitor Therapy
Published in
Frontiers in oncology, August 2021
DOI 10.3389/fonc.2021.590937
Pubmed ID
Authors

Qiaoyou Weng, Junguo Hui, Hailin Wang, Chuanqiang Lan, Jiansheng Huang, Chun Zhao, Liyun Zheng, Shiji Fang, Minjiang Chen, Chenying Lu, Yuyan Bao, Peipei Pang, Min Xu, Weibo Mao, Zufei Wang, Jianfei Tu, Yuan Huang, Jiansong Ji

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

Geographical breakdown

Country Count As %
Unknown 8 100%

Demographic breakdown

Readers by professional status Count As %
Other 1 13%
Researcher 1 13%
Student > Doctoral Student 1 13%
Lecturer > Senior Lecturer 1 13%
Unknown 4 50%
Readers by discipline Count As %
Computer Science 2 25%
Medicine and Dentistry 2 25%
Unknown 4 50%
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 August 2021.
All research outputs
#22,774,430
of 25,392,582 outputs
Outputs from Frontiers in oncology
#15,926
of 22,436 outputs
Outputs of similar age
#376,862
of 438,073 outputs
Outputs of similar age from Frontiers in oncology
#840
of 1,340 outputs
Altmetric has tracked 25,392,582 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 22,436 research outputs from this source. They receive a mean Attention Score of 3.0. 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 438,073 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 1,340 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.