↓ Skip to main content

Investigation of a Novel Deep Learning-Based Computed Tomography Perfusion Mapping Framework for Functional Lung Avoidance Radiotherapy

Overview of attention for article published in Frontiers in oncology, March 2021
Altmetric Badge

Mentioned by

twitter
1 X user

Citations

dimensions_citation
13 Dimensions

Readers on

mendeley
38 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Investigation of a Novel Deep Learning-Based Computed Tomography Perfusion Mapping Framework for Functional Lung Avoidance Radiotherapy
Published in
Frontiers in oncology, March 2021
DOI 10.3389/fonc.2021.644703
Pubmed ID
Authors

Ge Ren, Sai-kit Lam, Jiang Zhang, Haonan Xiao, Andy Lai-yin Cheung, Wai-yin Ho, Jing Qin, Jing Cai

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

Geographical breakdown

Country Count As %
Unknown 38 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 7 18%
Student > Master 5 13%
Student > Ph. D. Student 3 8%
Other 2 5%
Student > Bachelor 2 5%
Other 2 5%
Unknown 17 45%
Readers by discipline Count As %
Medicine and Dentistry 6 16%
Computer Science 4 11%
Physics and Astronomy 3 8%
Engineering 2 5%
Nursing and Health Professions 1 3%
Other 1 3%
Unknown 21 55%
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 29 April 2021.
All research outputs
#23,487,873
of 26,163,973 outputs
Outputs from Frontiers in oncology
#16,353
of 22,913 outputs
Outputs of similar age
#398,389
of 459,065 outputs
Outputs of similar age from Frontiers in oncology
#763
of 1,075 outputs
Altmetric has tracked 26,163,973 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 22,913 research outputs from this source. They receive a mean Attention Score of 3.1. 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 459,065 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 1,075 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.