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Medical image analysis using deep learning algorithms

Overview of attention for article published in Frontiers in Public Health, November 2023
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age and source (59th percentile)

Mentioned by

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2 X users

Citations

dimensions_citation
14 Dimensions

Readers on

mendeley
149 Mendeley
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Title
Medical image analysis using deep learning algorithms
Published in
Frontiers in Public Health, November 2023
DOI 10.3389/fpubh.2023.1273253
Pubmed ID
Authors

Mengfang Li, Yuanyuan Jiang, Yanzhou Zhang, Haisheng Zhu

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

Geographical breakdown

Country Count As %
Unknown 149 100%

Demographic breakdown

Readers by professional status Count As %
Unspecified 36 24%
Student > Ph. D. Student 15 10%
Student > Master 14 9%
Student > Doctoral Student 4 3%
Lecturer 3 2%
Other 10 7%
Unknown 67 45%
Readers by discipline Count As %
Unspecified 37 25%
Computer Science 16 11%
Engineering 8 5%
Medicine and Dentistry 6 4%
Pharmacology, Toxicology and Pharmaceutical Science 4 3%
Other 7 5%
Unknown 71 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 08 November 2023.
All research outputs
#19,845,534
of 25,263,619 outputs
Outputs from Frontiers in Public Health
#6,737
of 13,789 outputs
Outputs of similar age
#231,796
of 349,027 outputs
Outputs of similar age from Frontiers in Public Health
#290
of 823 outputs
Altmetric has tracked 25,263,619 research outputs across all sources so far. This one is in the 18th percentile – i.e., 18% of other outputs scored the same or lower than it.
So far Altmetric has tracked 13,789 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.4. This one is in the 44th percentile – i.e., 44% 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 349,027 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 823 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 59% of its contemporaries.