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Predicting clinical outcomes among hospitalized COVID-19 patients using both local and published models

Overview of attention for article published in BMC Medical Informatics and Decision Making, July 2021
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  • Average Attention Score compared to outputs of the same age and source

Mentioned by

twitter
3 X users

Citations

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13 Dimensions

Readers on

mendeley
27 Mendeley
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Title
Predicting clinical outcomes among hospitalized COVID-19 patients using both local and published models
Published in
BMC Medical Informatics and Decision Making, July 2021
DOI 10.1186/s12911-021-01576-w
Pubmed ID
Authors

William Galanter, Jorge Mario Rodríguez-Fernández, Kevin Chow, Samuel Harford, Karl M. Kochendorfer, Maryam Pishgar, Julian Theis, John Zulueta, Houshang Darabi

X Demographics

X Demographics

The data shown below were collected from the profiles of 3 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 27 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 27 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 3 11%
Student > Master 3 11%
Other 2 7%
Librarian 2 7%
Student > Bachelor 1 4%
Other 3 11%
Unknown 13 48%
Readers by discipline Count As %
Medicine and Dentistry 5 19%
Nursing and Health Professions 2 7%
Biochemistry, Genetics and Molecular Biology 1 4%
Pharmacology, Toxicology and Pharmaceutical Science 1 4%
Environmental Science 1 4%
Other 4 15%
Unknown 13 48%
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 01 August 2021.
All research outputs
#14,555,398
of 23,310,485 outputs
Outputs from BMC Medical Informatics and Decision Making
#1,124
of 2,024 outputs
Outputs of similar age
#219,326
of 436,492 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#38
of 62 outputs
Altmetric has tracked 23,310,485 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 2,024 research outputs from this source. They receive a mean Attention Score of 4.9. This one is in the 38th percentile – i.e., 38% of its peers scored the same or lower than it.
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 436,492 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 46th percentile – i.e., 46% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 62 others from the same source and published within six weeks on either side of this one. This one is in the 35th percentile – i.e., 35% of its contemporaries scored the same or lower than it.