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AAPM task group report 273: Recommendations on best practices for AI and machine learning for computer‐aided diagnosis in medical imaging

Overview of attention for article published in Medical Physics, January 2023
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (74th percentile)
  • High Attention Score compared to outputs of the same age and source (92nd percentile)

Mentioned by

twitter
6 tweeters

Citations

dimensions_citation
1 Dimensions

Readers on

mendeley
7 Mendeley
Summary Twitter Dimensions citations
Title
AAPM task group report 273: Recommendations on best practices for AI and machine learning for computer‐aided diagnosis in medical imaging
Published in
Medical Physics, January 2023
DOI 10.1002/mp.16188
Pubmed ID
36565447
Authors

Lubomir Hadjiiski, Kenny Cha, Heang‐Ping Chan, Karen Drukker, Lia Morra, Janne J. Näppi, Berkman Sahiner, Hiroyuki Yoshida, Quan Chen, Thomas M. Deserno, Hayit Greenspan, Henkjan Huisman, Zhimin Huo, Richard Mazurchuk, Nicholas Petrick, Daniele Regge, Ravi Samala, Ronald M. Summers, Kenji Suzuki, Georgia Tourassi, Daniel Vergara, Samuel G. Armato

View on publisher site

Twitter Demographics

The data shown below were collected from the profiles of 6 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 7 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 7 100%

Demographic breakdown

Readers by professional status Count As %
Other 2 29%
Researcher 2 29%
Student > Ph. D. Student 1 14%
Unknown 2 29%
Readers by discipline Count As %
Medicine and Dentistry 3 43%
Physics and Astronomy 2 29%
Neuroscience 1 14%
Unknown 1 14%

Attention Score in Context

This research output has an Altmetric Attention Score of 5. 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 March 2023.
All research outputs
#6,261,003
of 23,299,593 outputs
Outputs from Medical Physics
#1,550
of 7,792 outputs
Outputs of similar age
#105,633
of 421,650 outputs
Outputs of similar age from Medical Physics
#8
of 106 outputs
Altmetric has tracked 23,299,593 research outputs across all sources so far. This one has received more attention than most of these and is in the 73rd percentile.
So far Altmetric has tracked 7,792 research outputs from this source. They receive a mean Attention Score of 3.4. This one has done well, scoring higher than 79% 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 421,650 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 74% of its contemporaries.
We're also able to compare this research output to 106 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 92% of its contemporaries.

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