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X Demographics
Mendeley readers
Attention Score in Context
Title |
Shortcut learning in medical AI hinders generalization: method for estimating AI model generalization without external data
|
---|---|
Published in |
npj Digital Medicine, May 2024
|
DOI | 10.1038/s41746-024-01118-4 |
Pubmed ID | |
Authors |
Cathy Ong Ly, Balagopal Unnikrishnan, Tony Tadic, Tirth Patel, Joe Duhamel, Sonja Kandel, Yasbanoo Moayedi, Michael Brudno, Andrew Hope, Heather Ross, Chris McIntosh |
X Demographics
The data shown below were collected from the profiles of 18 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
Country | Count | As % |
---|---|---|
Canada | 6 | 33% |
United States | 3 | 17% |
Thailand | 1 | 6% |
Spain | 1 | 6% |
Taiwan | 1 | 6% |
Germany | 1 | 6% |
Unknown | 5 | 28% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 12 | 67% |
Scientists | 4 | 22% |
Science communicators (journalists, bloggers, editors) | 2 | 11% |
Mendeley readers
The data shown below were compiled from readership statistics for 1 Mendeley reader of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 1 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Master | 1 | 100% |
Readers by discipline | Count | As % |
---|---|---|
Engineering | 1 | 100% |
Attention Score in Context
This research output has an Altmetric Attention Score of 11. 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 16 May 2024.
All research outputs
#3,370,323
of 25,916,093 outputs
Outputs from npj Digital Medicine
#663
of 1,057 outputs
Outputs of similar age
#19,463
of 154,287 outputs
Outputs of similar age from npj Digital Medicine
#14
of 43 outputs
Altmetric has tracked 25,916,093 research outputs across all sources so far. Compared to these this one has done well and is in the 86th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,057 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 53.7. This one is in the 36th percentile – i.e., 36% 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 154,287 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 87% of its contemporaries.
We're also able to compare this research output to 43 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.