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Deep Learning With Radiomics for Disease Diagnosis and Treatment: Challenges and Potential

Overview of attention for article published in Frontiers in oncology, February 2022
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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 (71st percentile)

Mentioned by

twitter
3 X users

Citations

dimensions_citation
77 Dimensions

Readers on

mendeley
135 Mendeley
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Title
Deep Learning With Radiomics for Disease Diagnosis and Treatment: Challenges and Potential
Published in
Frontiers in oncology, February 2022
DOI 10.3389/fonc.2022.773840
Pubmed ID
Authors

Xingping Zhang, Yanchun Zhang, Guijuan Zhang, Xingting Qiu, Wenjun Tan, Xiaoxia Yin, Liefa Liao

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

Geographical breakdown

Country Count As %
Unknown 135 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 24 18%
Researcher 8 6%
Student > Master 8 6%
Student > Bachelor 6 4%
Student > Doctoral Student 4 3%
Other 17 13%
Unknown 68 50%
Readers by discipline Count As %
Computer Science 17 13%
Engineering 11 8%
Medicine and Dentistry 10 7%
Nursing and Health Professions 4 3%
Physics and Astronomy 4 3%
Other 15 11%
Unknown 74 55%
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 08 March 2022.
All research outputs
#16,589,826
of 26,166,431 outputs
Outputs from Frontiers in oncology
#5,842
of 22,913 outputs
Outputs of similar age
#240,455
of 454,608 outputs
Outputs of similar age from Frontiers in oncology
#371
of 1,568 outputs
Altmetric has tracked 26,166,431 research outputs across all sources so far. This one is in the 34th percentile – i.e., 34% 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 70% 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 454,608 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 43rd percentile – i.e., 43% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 1,568 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 71% of its contemporaries.