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Classification of IHC Images of NATs With ResNet-FRP-LSTM for Predicting Survival Rates of Rectal Cancer Patients

Overview of attention for article published in IEEE Journal of Translational Engineering in Health and Medicine, December 2022
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Mentioned by

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1 X user

Citations

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4 Dimensions

Readers on

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16 Mendeley
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Title
Classification of IHC Images of NATs With ResNet-FRP-LSTM for Predicting Survival Rates of Rectal Cancer Patients
Published in
IEEE Journal of Translational Engineering in Health and Medicine, December 2022
DOI 10.1109/jtehm.2022.3229561
Pubmed ID
Authors

Tuan D. Pham, Vinayakumar Ravi, Chuanwen Fan, Bin Luo, Xiao-Feng Sun

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 16 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 16 100%

Demographic breakdown

Readers by professional status Count As %
Unspecified 3 19%
Lecturer 1 6%
Student > Doctoral Student 1 6%
Unknown 11 69%
Readers by discipline Count As %
Unspecified 3 19%
Computer Science 1 6%
Medicine and Dentistry 1 6%
Unknown 11 69%
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 27 January 2023.
All research outputs
#22,778,604
of 25,392,582 outputs
Outputs from IEEE Journal of Translational Engineering in Health and Medicine
#205
of 228 outputs
Outputs of similar age
#409,940
of 480,152 outputs
Outputs of similar age from IEEE Journal of Translational Engineering in Health and Medicine
#8
of 8 outputs
Altmetric has tracked 25,392,582 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 228 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.0. 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 480,152 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 8 others from the same source and published within six weeks on either side of this one.