↓ Skip to main content

Prostate Cancer Risk Stratification via Nondestructive 3D Pathology with Deep Learning–Assisted Gland Analysis

Overview of attention for article published in Cancer Research, December 2021
Altmetric Badge

About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#28 of 18,742)
  • High Attention Score compared to outputs of the same age (99th percentile)
  • High Attention Score compared to outputs of the same age and source (99th percentile)

Mentioned by

news
66 news outlets
blogs
6 blogs
twitter
45 tweeters

Citations

dimensions_citation
33 Dimensions

Readers on

mendeley
63 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Prostate Cancer Risk Stratification via Nondestructive 3D Pathology with Deep Learning–Assisted Gland Analysis
Published in
Cancer Research, December 2021
DOI 10.1158/0008-5472.can-21-2843
Pubmed ID
Authors

Weisi Xie, Nicholas P. Reder, Can Koyuncu, Patrick Leo, Sarah Hawley, Hongyi Huang, Chenyi Mao, Nadia Postupna, Soyoung Kang, Robert Serafin, Gan Gao, Qinghua Han, Kevin W. Bishop, Lindsey A. Barner, Pingfu Fu, Jonathan L. Wright, C. Dirk Keene, Joshua C. Vaughan, Andrew Janowczyk, Adam K. Glaser, Anant Madabhushi, Lawrence D. True, Jonathan T.C. Liu

Twitter Demographics

Twitter Demographics

The data shown below were collected from the profiles of 45 tweeters 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 63 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 63 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 12 19%
Student > Ph. D. Student 8 13%
Student > Bachelor 8 13%
Student > Doctoral Student 4 6%
Unspecified 3 5%
Other 8 13%
Unknown 20 32%
Readers by discipline Count As %
Engineering 12 19%
Agricultural and Biological Sciences 6 10%
Medicine and Dentistry 5 8%
Biochemistry, Genetics and Molecular Biology 4 6%
Physics and Astronomy 3 5%
Other 11 17%
Unknown 22 35%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 518. 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 23 November 2022.
All research outputs
#45,083
of 24,294,722 outputs
Outputs from Cancer Research
#28
of 18,742 outputs
Outputs of similar age
#1,389
of 509,683 outputs
Outputs of similar age from Cancer Research
#1
of 100 outputs
Altmetric has tracked 24,294,722 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 99th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 18,742 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 9.2. This one has done particularly well, scoring higher than 99% 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 509,683 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 99% of its contemporaries.
We're also able to compare this research output to 100 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 99% of its contemporaries.