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OrganoIDNet: a deep learning tool for identification of therapeutic effects in PDAC organoid-PBMC co-cultures from time-resolved imaging data

Overview of attention for article published in Cellular Oncology, May 2024
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#28 of 480)
  • High Attention Score compared to outputs of the same age (86th percentile)
  • High Attention Score compared to outputs of the same age and source (85th percentile)

Mentioned by

blogs
1 blog
twitter
5 X users

Citations

dimensions_citation
4 Dimensions

Readers on

mendeley
4 Mendeley
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Title
OrganoIDNet: a deep learning tool for identification of therapeutic effects in PDAC organoid-PBMC co-cultures from time-resolved imaging data
Published in
Cellular Oncology, May 2024
DOI 10.1007/s13402-024-00958-2
Pubmed ID
Authors

Nathalia Ferreira, Ajinkya Kulkarni, David Agorku, Teona Midelashvili, Olaf Hardt, Tobias J. Legler, Philipp Ströbel, Lena-Christin Conradi, Frauke Alves, Fernanda Ramos-Gomes, M. Andrea Markus

Timeline

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X Demographics

X Demographics

The data shown below were collected from the profiles of 5 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 4 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 4 100%

Demographic breakdown

Readers by professional status Count As %
Professor 1 25%
Student > Ph. D. Student 1 25%
Researcher 1 25%
Unknown 1 25%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 3 75%
Unknown 1 25%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 10. 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 07 June 2024.
All research outputs
#3,731,451
of 26,101,087 outputs
Outputs from Cellular Oncology
#28
of 480 outputs
Outputs of similar age
#25,267
of 184,640 outputs
Outputs of similar age from Cellular Oncology
#1
of 7 outputs
Altmetric has tracked 26,101,087 research outputs across all sources so far. Compared to these this one has done well and is in the 85th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 480 research outputs from this source. They receive a mean Attention Score of 3.6. This one has done particularly well, scoring higher than 94% 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 184,640 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 86% of its contemporaries.
We're also able to compare this research output to 7 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them