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Predicting the Local Response of Metastatic Brain Tumor to Gamma Knife Radiosurgery by Radiomics With a Machine Learning Method

Overview of attention for article published in Frontiers in oncology, January 2021
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  • Average Attention Score compared to outputs of the same age and source

Mentioned by

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3 X users

Citations

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31 Dimensions

Readers on

mendeley
30 Mendeley
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Title
Predicting the Local Response of Metastatic Brain Tumor to Gamma Knife Radiosurgery by Radiomics With a Machine Learning Method
Published in
Frontiers in oncology, January 2021
DOI 10.3389/fonc.2020.569461
Pubmed ID
Authors

Daisuke Kawahara, Xueyan Tang, Chung K. Lee, Yasushi Nagata, Yoichi Watanabe

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

Geographical breakdown

Country Count As %
Unknown 30 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 5 17%
Student > Bachelor 4 13%
Researcher 3 10%
Student > Doctoral Student 1 3%
Lecturer 1 3%
Other 5 17%
Unknown 11 37%
Readers by discipline Count As %
Medicine and Dentistry 9 30%
Computer Science 3 10%
Environmental Science 1 3%
Biochemistry, Genetics and Molecular Biology 1 3%
Nursing and Health Professions 1 3%
Other 2 7%
Unknown 13 43%
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 17 February 2021.
All research outputs
#19,957,118
of 25,387,668 outputs
Outputs from Frontiers in oncology
#9,330
of 22,433 outputs
Outputs of similar age
#378,402
of 521,732 outputs
Outputs of similar age from Frontiers in oncology
#306
of 698 outputs
Altmetric has tracked 25,387,668 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 22,433 research outputs from this source. They receive a mean Attention Score of 3.0. 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 521,732 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 23rd percentile – i.e., 23% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 698 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 50% of its contemporaries.