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A Dataset of Pulmonary Lesions With Multiple-Level Attributes and Fine Contours

Overview of attention for article published in Frontiers in Digital Health, February 2021
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  • Average Attention Score compared to outputs of the same age
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

twitter
2 X users

Citations

dimensions_citation
1 Dimensions

Readers on

mendeley
5 Mendeley
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Title
A Dataset of Pulmonary Lesions With Multiple-Level Attributes and Fine Contours
Published in
Frontiers in Digital Health, February 2021
DOI 10.3389/fdgth.2020.609349
Pubmed ID
Authors

Ping Li, Xiangwen Kong, Johann Li, Guangming Zhu, Xiaoyuan Lu, Peiyi Shen, Syed Afaq Ali Shah, Mohammed Bennamoun, Tao Hua

X Demographics

X Demographics

The data shown below were collected from the profiles of 2 X users 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 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 > Master 2 40%
Student > Ph. D. Student 1 20%
Unspecified 1 20%
Unknown 1 20%
Readers by discipline Count As %
Computer Science 2 40%
Unspecified 1 20%
Physics and Astronomy 1 20%
Unknown 1 20%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 29 October 2021.
All research outputs
#14,539,338
of 23,283,373 outputs
Outputs from Frontiers in Digital Health
#379
of 575 outputs
Outputs of similar age
#230,336
of 420,998 outputs
Outputs of similar age from Frontiers in Digital Health
#27
of 44 outputs
Altmetric has tracked 23,283,373 research outputs across all sources so far. This one is in the 35th percentile – i.e., 35% of other outputs scored the same or lower than it.
So far Altmetric has tracked 575 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 11.5. This one is in the 30th percentile – i.e., 30% 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 420,998 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 42nd percentile – i.e., 42% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 44 others from the same source and published within six weeks on either side of this one. This one is in the 38th percentile – i.e., 38% of its contemporaries scored the same or lower than it.