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Development of a quantitative segmentation model to assess the effect of comorbidity on patients with COVID-19

Overview of attention for article published in European Journal of Medical Research, October 2020
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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 (76th percentile)

Mentioned by

twitter
6 tweeters

Citations

dimensions_citation
2 Dimensions

Readers on

mendeley
79 Mendeley
Title
Development of a quantitative segmentation model to assess the effect of comorbidity on patients with COVID-19
Published in
European Journal of Medical Research, October 2020
DOI 10.1186/s40001-020-00450-1
Pubmed ID
Authors

Cui Zhang, Guangzhao Yang, Chunxian Cai, Zhihua Xu, Hai Wu, Youmin Guo, Zongyu Xie, Hengfeng Shi, Guohua Cheng, Jian Wang

Twitter Demographics

The data shown below were collected from the profiles of 6 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 79 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 79 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 11 14%
Researcher 10 13%
Student > Bachelor 8 10%
Other 5 6%
Student > Ph. D. Student 5 6%
Other 17 22%
Unknown 23 29%
Readers by discipline Count As %
Medicine and Dentistry 18 23%
Nursing and Health Professions 7 9%
Computer Science 6 8%
Engineering 5 6%
Biochemistry, Genetics and Molecular Biology 4 5%
Other 15 19%
Unknown 24 30%

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 18 February 2021.
All research outputs
#11,368,866
of 18,679,853 outputs
Outputs from European Journal of Medical Research
#172
of 414 outputs
Outputs of similar age
#211,018
of 387,363 outputs
Outputs of similar age from European Journal of Medical Research
#12
of 56 outputs
Altmetric has tracked 18,679,853 research outputs across all sources so far. This one is in the 37th percentile – i.e., 37% of other outputs scored the same or lower than it.
So far Altmetric has tracked 414 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.4. This one has gotten more attention than average, scoring higher than 56% 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 387,363 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 42nd percentile – i.e., 42% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 56 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 76% of its contemporaries.