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Predictive model for acute respiratory distress syndrome events in ICU patients in China using machine learning algorithms: a secondary analysis of a cohort study

Overview of attention for article published in Journal of Translational Medicine, October 2019
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (60th percentile)

Mentioned by

patent
1 patent

Citations

dimensions_citation
20 Dimensions

Readers on

mendeley
47 Mendeley
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Title
Predictive model for acute respiratory distress syndrome events in ICU patients in China using machine learning algorithms: a secondary analysis of a cohort study
Published in
Journal of Translational Medicine, October 2019
DOI 10.1186/s12967-019-2075-0
Pubmed ID
Authors

Xian-Fei Ding, Jin-Bo Li, Huo-Yan Liang, Zong-Yu Wang, Ting-Ting Jiao, Zhuang Liu, Liang Yi, Wei-Shuai Bian, Shu-Peng Wang, Xi Zhu, Tong-Wen Sun

Mendeley readers

The data shown below were compiled from readership statistics for 47 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 47 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 7 15%
Researcher 6 13%
Student > Ph. D. Student 4 9%
Student > Master 3 6%
Student > Doctoral Student 2 4%
Other 8 17%
Unknown 17 36%
Readers by discipline Count As %
Medicine and Dentistry 10 21%
Computer Science 7 15%
Nursing and Health Professions 3 6%
Business, Management and Accounting 2 4%
Mathematics 1 2%
Other 4 9%
Unknown 20 43%

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 April 2021.
All research outputs
#6,811,449
of 20,999,751 outputs
Outputs from Journal of Translational Medicine
#1,106
of 3,629 outputs
Outputs of similar age
#127,992
of 338,529 outputs
Outputs of similar age from Journal of Translational Medicine
#1
of 1 outputs
Altmetric has tracked 20,999,751 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% of other outputs scored the same or lower than it.
So far Altmetric has tracked 3,629 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.1. This one has gotten more attention than average, scoring higher than 64% 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 338,529 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 60% of its contemporaries.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them