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Analysis of EPID Transmission Fluence Maps Using Machine Learning Models and CNN for Identifying Position Errors in the Treatment of GO Patients

Overview of attention for article published in Frontiers in oncology, September 2021
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About this Attention Score

  • Average Attention Score compared to outputs of the same age
  • Good Attention Score compared to outputs of the same age and source (67th percentile)

Mentioned by

twitter
2 X users

Citations

dimensions_citation
6 Dimensions

Readers on

mendeley
12 Mendeley
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Title
Analysis of EPID Transmission Fluence Maps Using Machine Learning Models and CNN for Identifying Position Errors in the Treatment of GO Patients
Published in
Frontiers in oncology, September 2021
DOI 10.3389/fonc.2021.721591
Pubmed ID
Authors

Guyu Dai, Xiangbin Zhang, Wenjie Liu, Zhibin Li, Guangyu Wang, Yaxin Liu, Qing Xiao, Lian Duan, Jing Li, Xinyu Song, Guangjun Li, Sen Bai

X Demographics

X Demographics

The data shown below were collected from the profiles of 2 X users 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 12 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 12 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 2 17%
Student > Bachelor 1 8%
Student > Master 1 8%
Researcher 1 8%
Professor > Associate Professor 1 8%
Other 0 0%
Unknown 6 50%
Readers by discipline Count As %
Medicine and Dentistry 2 17%
Physics and Astronomy 2 17%
Agricultural and Biological Sciences 1 8%
Unknown 7 58%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 01 October 2021.
All research outputs
#17,285,374
of 26,163,973 outputs
Outputs from Frontiers in oncology
#6,849
of 22,913 outputs
Outputs of similar age
#251,890
of 438,399 outputs
Outputs of similar age from Frontiers in oncology
#358
of 1,400 outputs
Altmetric has tracked 26,163,973 research outputs across all sources so far. This one is in the 31st percentile – i.e., 31% of other outputs scored the same or lower than it.
So far Altmetric has tracked 22,913 research outputs from this source. They receive a mean Attention Score of 3.1. This one has gotten more attention than average, scoring higher than 64% 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 438,399 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 39th percentile – i.e., 39% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 1,400 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 67% of its contemporaries.