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A Deep Learning Model for the Diagnosis and Discrimination of Gram-Positive and Gram-Negative Bacterial Pneumonia for Children Using Chest Radiography Images and Clinical Information

Overview of attention for article published in Infection and Drug Resistance, June 2023
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Mentioned by

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1 X user

Citations

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6 Dimensions

Readers on

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6 Mendeley
Title
A Deep Learning Model for the Diagnosis and Discrimination of Gram-Positive and Gram-Negative Bacterial Pneumonia for Children Using Chest Radiography Images and Clinical Information
Published in
Infection and Drug Resistance, June 2023
DOI 10.2147/idr.s404786
Pubmed ID
Authors

Ru Wen, Peng Xu, Yimin Cai, Fang Wang, Mengfei Li, Xianchun Zeng, Chen Liu

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.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 6 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 6 100%

Demographic breakdown

Readers by professional status Count As %
Unspecified 2 33%
Lecturer 1 17%
Unknown 3 50%
Readers by discipline Count As %
Unspecified 2 33%
Engineering 1 17%
Unknown 3 50%
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 25 June 2023.
All research outputs
#21,446,763
of 23,942,155 outputs
Outputs from Infection and Drug Resistance
#1,430
of 1,857 outputs
Outputs of similar age
#223,462
of 269,038 outputs
Outputs of similar age from Infection and Drug Resistance
#47
of 63 outputs
Altmetric has tracked 23,942,155 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 1,857 research outputs from this source. They receive a mean Attention Score of 4.6. 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 269,038 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 63 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.