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Benchmarking foundation models as feature extractors for weakly supervised computational pathology

Overview of attention for article published in Nature Biomedical Engineering, October 2025
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reddit
1 Redditor
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1 Bluesky user

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mendeley
105 Mendeley
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Article details
Title
Benchmarking foundation models as feature extractors for weakly supervised computational pathology
Published in
Nature Biomedical Engineering, October 2025
DOI 10.1038/s41551-025-01516-3
Pubmed ID
Authors

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Timeline Attention over time Attention Score history
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Mendeley demographics

Mendeley demographics

The data shown below were compiled from readership statistics for 105 Mendeley readers of this research output. Click here to see the associated Mendeley record.
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Geographical breakdown

Geographical breakdown
Country Count As %
Unknown 105 100%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Student > Ph. D. Student 12 11%
Researcher 11 10%
Student > Master 7 7%
Other 5 5%
Professor 4 4%
Other 12 11%
Unknown 54 51%
Readers by discipline
Readers by discipline Count As %
Computer Science 14 13%
Biochemistry, Genetics and Molecular Biology 9 9%
Medicine and Dentistry 9 9%
Engineering 8 8%
Agricultural and Biological Sciences 3 3%
Other 6 6%
Unknown 56 53%
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 19 August 2026.
All research outputs
#27,693,281
of 34,351,437 outputs
Outputs from Nature Biomedical Engineering
#1,594
of 1,684 outputs
Outputs of similar age
#234,082
of 355,315 outputs
Outputs of similar age from Nature Biomedical Engineering
#61
of 67 outputs
Altmetric has tracked 34,351,437 research outputs across all sources so far. This one is in the 16th percentile – i.e., 16% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,684 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 75.0. This one is in the 4th percentile – i.e., 4% 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 355,315 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 67 others from the same source and published within six weeks on either side of this one. This one is in the 5th percentile – i.e., 5% of its contemporaries scored the same or lower than it.