↓ Skip to main content

Development, Validation, and Comparison of Image-Based, Clinical Feature-Based and Fusion Artificial Intelligence Diagnostic Models in Differentiating Benign and Malignant Pulmonary Ground-Glass…

Overview of attention for article published in Frontiers in oncology, June 2022
Altmetric Badge

About this Attention Score

  • Above-average Attention Score compared to outputs of the same age and source (61st percentile)

Mentioned by

twitter
4 X users

Readers on

mendeley
5 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
Development, Validation, and Comparison of Image-Based, Clinical Feature-Based and Fusion Artificial Intelligence Diagnostic Models in Differentiating Benign and Malignant Pulmonary Ground-Glass Nodules
Published in
Frontiers in oncology, June 2022
DOI 10.3389/fonc.2022.892890
Pubmed ID
Authors

Xiang Wang, Man Gao, Jicai Xie, Yanfang Deng, Wenting Tu, Hua Yang, Shuang Liang, Panlong Xu, Mingzi Zhang, Yang Lu, ChiCheng Fu, Qiong Li, Li Fan, Shiyuan Liu

Timeline

Login to access the full chart related to this output.

If you don’t have an account, click here to discover Explorer

X Demographics

X Demographics

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

Geographical breakdown

Country Count As %
Unknown 5 100%

Demographic breakdown

Readers by professional status Count As %
Student > Doctoral Student 1 20%
Student > Ph. D. Student 1 20%
Researcher 1 20%
Other 1 20%
Unknown 1 20%
Readers by discipline Count As %
Arts and Humanities 1 20%
Computer Science 1 20%
Social Sciences 1 20%
Engineering 1 20%
Unknown 1 20%
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 26 June 2022.
All research outputs
#17,881,371
of 26,178,577 outputs
Outputs from Frontiers in oncology
#8,278
of 22,922 outputs
Outputs of similar age
#269,535
of 452,615 outputs
Outputs of similar age from Frontiers in oncology
#583
of 1,692 outputs
Altmetric has tracked 26,178,577 research outputs across all sources so far. This one is in the 21st percentile – i.e., 21% of other outputs scored the same or lower than it.
So far Altmetric has tracked 22,922 research outputs from this source. They receive a mean Attention Score of 3.1. This one has gotten more attention than average, scoring higher than 58% 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 452,615 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 29th percentile – i.e., 29% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 1,692 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 61% of its contemporaries.