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Predicting Adverse Drug Events in Chinese Pediatric Inpatients With the Associated Risk Factors: A Machine Learning Study

Overview of attention for article published in Frontiers in Pharmacology, April 2021
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About this Attention Score

  • Average Attention Score compared to outputs of the same age
  • Good Attention Score compared to outputs of the same age and source (67th percentile)

Mentioned by

twitter
4 X users

Citations

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26 Dimensions

Readers on

mendeley
34 Mendeley
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Title
Predicting Adverse Drug Events in Chinese Pediatric Inpatients With the Associated Risk Factors: A Machine Learning Study
Published in
Frontiers in Pharmacology, April 2021
DOI 10.3389/fphar.2021.659099
Pubmed ID
Authors

Ze Yu, Huanhuan Ji, Jianwen Xiao, Ping Wei, Lin Song, Tingting Tang, Xin Hao, Jinyuan Zhang, Qiaona Qi, Yuchen Zhou, Fei Gao, Yuntao Jia

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

Geographical breakdown

Country Count As %
Unknown 34 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 4 12%
Student > Ph. D. Student 3 9%
Student > Master 2 6%
Lecturer > Senior Lecturer 1 3%
Professor 1 3%
Other 3 9%
Unknown 20 59%
Readers by discipline Count As %
Computer Science 5 15%
Pharmacology, Toxicology and Pharmaceutical Science 2 6%
Biochemistry, Genetics and Molecular Biology 1 3%
Unspecified 1 3%
Business, Management and Accounting 1 3%
Other 3 9%
Unknown 21 62%
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 14 May 2021.
All research outputs
#14,554,120
of 23,308,124 outputs
Outputs from Frontiers in Pharmacology
#4,888
of 16,753 outputs
Outputs of similar age
#227,831
of 437,171 outputs
Outputs of similar age from Frontiers in Pharmacology
#265
of 889 outputs
Altmetric has tracked 23,308,124 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 16,753 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.0. This one has gotten more attention than average, scoring higher than 68% 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 437,171 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 44th percentile – i.e., 44% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 889 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 67% of its contemporaries.