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Does a Deep Learning–Based Computer-Assisted Diagnosis System Outperform Conventional Double Reading by Radiologists in Distinguishing Benign and Malignant Lung Nodules?

Overview of attention for article published in Frontiers in oncology, October 2020
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Mentioned by

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1 X user

Citations

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8 Dimensions

Readers on

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21 Mendeley
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Title
Does a Deep Learning–Based Computer-Assisted Diagnosis System Outperform Conventional Double Reading by Radiologists in Distinguishing Benign and Malignant Lung Nodules?
Published in
Frontiers in oncology, October 2020
DOI 10.3389/fonc.2020.545862
Pubmed ID
Authors

Zhou Liu, Li Li, Tianran Li, Douqiang Luo, Xiaoliang Wang, Dehong Luo

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

Geographical breakdown

Country Count As %
Unknown 21 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 6 29%
Other 2 10%
Professor 2 10%
Unspecified 1 5%
Student > Bachelor 1 5%
Other 2 10%
Unknown 7 33%
Readers by discipline Count As %
Medicine and Dentistry 7 33%
Business, Management and Accounting 1 5%
Unspecified 1 5%
Computer Science 1 5%
Engineering 1 5%
Other 0 0%
Unknown 10 48%
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 10 November 2020.
All research outputs
#22,771,990
of 25,387,668 outputs
Outputs from Frontiers in oncology
#15,926
of 22,433 outputs
Outputs of similar age
#376,647
of 436,151 outputs
Outputs of similar age from Frontiers in oncology
#415
of 662 outputs
Altmetric has tracked 25,387,668 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 22,433 research outputs from this source. They receive a mean Attention Score of 3.0. 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 436,151 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 662 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.