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Feasibility and effectiveness of automatic deep learning network and radiomics models for differentiating tumor stroma ratio in pancreatic ductal adenocarcinoma

Overview of attention for article published in Insights into Imaging, December 2023
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1 X user

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4 Mendeley
Title
Feasibility and effectiveness of automatic deep learning network and radiomics models for differentiating tumor stroma ratio in pancreatic ductal adenocarcinoma
Published in
Insights into Imaging, December 2023
DOI 10.1186/s13244-023-01553-z
Pubmed ID
Authors

Hongfan Liao, Jiang Yuan, Chunhua Liu, Jiao Zhang, Yaying Yang, Hongwei Liang, Song Jiang, Shanxiong Chen, Yongmei Li, Yanbing Liu

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
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 %
Researcher 2 50%
Unknown 2 50%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 1 25%
Unknown 3 75%
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 11 January 2024.
All research outputs
#22,542,717
of 25,147,320 outputs
Outputs from Insights into Imaging
#1,043
of 1,182 outputs
Outputs of similar age
#183,841
of 228,969 outputs
Outputs of similar age from Insights into Imaging
#26
of 37 outputs
Altmetric has tracked 25,147,320 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,182 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.1. This one is in the 1st percentile – i.e., 1% 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 228,969 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 37 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.