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The importance of association of comorbidities on COVID-19 outcomes: a machine learning approach

Overview of attention for article published in Current Medical Research & Opinion, February 2022
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (96th percentile)
  • High Attention Score compared to outputs of the same age and source (98th percentile)

Mentioned by

news
4 news outlets
blogs
1 blog
twitter
31 X users
facebook
1 Facebook page

Citations

dimensions_citation
5 Dimensions

Readers on

mendeley
81 Mendeley
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Title
The importance of association of comorbidities on COVID-19 outcomes: a machine learning approach
Published in
Current Medical Research & Opinion, February 2022
DOI 10.1080/03007995.2022.2029382
Pubmed ID
Authors

José Carlos Arévalo-Lorido, Juana Carretero-Gómez, Jose Manuel Casas-Rojo, Juan Miguel Antón-Santos, José Antonio Melero-Bermejo, Maria Dolores López-Carmona, Lidia Cobos Palacios, Jaime Sanz-Cánovas, Paula Maria Pesqueira-Fontán, Andrés Alberto de la Peña-Fernández, Navas-Maria de la Sierra Alcántara, Gema Maria García-García, José David Torres Peña, Jeffrey Oskar Magallanes-Gamboa, Rosa Fernández-Madera-Martinez, Javier Fernández-Fernández, Manuel Rubio-Rivas, Guillermo Maestro-de la Calle, Eva Cervilla-Muñoz, Antonio Ramos-Martínez, Manuel Méndez-Bailón, José Manuel Ramos-Rincón, Ricardo Gómez-Huelgas

X Demographics

X Demographics

The data shown below were collected from the profiles of 31 X users 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 81 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 81 100%

Demographic breakdown

Readers by professional status Count As %
Unspecified 13 16%
Student > Master 9 11%
Student > Ph. D. Student 7 9%
Lecturer 5 6%
Student > Bachelor 4 5%
Other 12 15%
Unknown 31 38%
Readers by discipline Count As %
Medicine and Dentistry 15 19%
Unspecified 13 16%
Pharmacology, Toxicology and Pharmaceutical Science 4 5%
Computer Science 3 4%
Immunology and Microbiology 3 4%
Other 10 12%
Unknown 33 41%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 53. 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 13 May 2022.
All research outputs
#798,964
of 25,392,582 outputs
Outputs from Current Medical Research & Opinion
#76
of 3,664 outputs
Outputs of similar age
#20,769
of 517,864 outputs
Outputs of similar age from Current Medical Research & Opinion
#1
of 52 outputs
Altmetric has tracked 25,392,582 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 96th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 3,664 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.1. This one has done particularly well, scoring higher than 97% 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 517,864 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 96% of its contemporaries.
We're also able to compare this research output to 52 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 98% of its contemporaries.