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Comparison and development of machine learning tools for the prediction of chronic obstructive pulmonary disease in the Chinese population

Overview of attention for article published in Journal of Translational Medicine, March 2020
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (71st percentile)
  • High Attention Score compared to outputs of the same age and source (80th percentile)

Mentioned by

blogs
1 blog

Citations

dimensions_citation
14 Dimensions

Readers on

mendeley
39 Mendeley
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Title
Comparison and development of machine learning tools for the prediction of chronic obstructive pulmonary disease in the Chinese population
Published in
Journal of Translational Medicine, March 2020
DOI 10.1186/s12967-020-02312-0
Pubmed ID
Authors

Xia Ma, Yanping Wu, Ling Zhang, Weilan Yuan, Li Yan, Sha Fan, Yunzhi Lian, Xia Zhu, Junhui Gao, Jiangman Zhao, Ping Zhang, Hui Tang, Weihua Jia

Mendeley readers

The data shown below were compiled from readership statistics for 39 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 39 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 4 10%
Other 3 8%
Student > Ph. D. Student 3 8%
Student > Doctoral Student 2 5%
Student > Master 2 5%
Other 6 15%
Unknown 19 49%
Readers by discipline Count As %
Computer Science 8 21%
Medicine and Dentistry 5 13%
Biochemistry, Genetics and Molecular Biology 2 5%
Unspecified 1 3%
Nursing and Health Professions 1 3%
Other 3 8%
Unknown 19 49%

Attention Score in Context

This research output has an Altmetric Attention Score of 6. 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 11 January 2022.
All research outputs
#5,376,741
of 21,546,315 outputs
Outputs from Journal of Translational Medicine
#804
of 3,730 outputs
Outputs of similar age
#134,389
of 468,752 outputs
Outputs of similar age from Journal of Translational Medicine
#71
of 358 outputs
Altmetric has tracked 21,546,315 research outputs across all sources so far. This one has received more attention than most of these and is in the 74th percentile.
So far Altmetric has tracked 3,730 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.2. This one has done well, scoring higher than 78% 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 468,752 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 71% of its contemporaries.
We're also able to compare this research output to 358 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 80% of its contemporaries.