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Can a Machine Learn from Radiologists’ Visual Search Behaviour and Their Interpretation of Mammograms—a Deep-Learning Study

Overview of attention for article published in Journal of Digital Imaging, August 2019
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Mentioned by

twitter
2 tweeters

Readers on

mendeley
8 Mendeley
Title
Can a Machine Learn from Radiologists’ Visual Search Behaviour and Their Interpretation of Mammograms—a Deep-Learning Study
Published in
Journal of Digital Imaging, August 2019
DOI 10.1007/s10278-018-00174-z
Pubmed ID
Authors

Suneeta Mall, Patrick C. Brennan, Claudia Mello-Thoms

Twitter Demographics

The data shown below were collected from the profiles of 2 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 8 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 8 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 3 38%
Professor > Associate Professor 1 13%
Researcher 1 13%
Student > Bachelor 1 13%
Student > Master 1 13%
Other 0 0%
Unknown 1 13%
Readers by discipline Count As %
Computer Science 3 38%
Psychology 1 13%
Nursing and Health Professions 1 13%
Decision Sciences 1 13%
Medicine and Dentistry 1 13%
Other 0 0%
Unknown 1 13%

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 15 August 2019.
All research outputs
#10,496,358
of 13,777,184 outputs
Outputs from Journal of Digital Imaging
#519
of 683 outputs
Outputs of similar age
#169,627
of 249,646 outputs
Outputs of similar age from Journal of Digital Imaging
#14
of 17 outputs
Altmetric has tracked 13,777,184 research outputs across all sources so far. This one is in the 20th percentile – i.e., 20% of other outputs scored the same or lower than it.
So far Altmetric has tracked 683 research outputs from this source. They receive a mean Attention Score of 4.6. This one is in the 16th percentile – i.e., 16% 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 249,646 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 27th percentile – i.e., 27% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 17 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.