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A process mining- deep learning approach to predict survival in a cohort of hospitalized COVID‐19 patients

Overview of attention for article published in BMC Medical Informatics and Decision Making, July 2022
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1 X user

Citations

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5 Dimensions

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26 Mendeley
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Title
A process mining- deep learning approach to predict survival in a cohort of hospitalized COVID‐19 patients
Published in
BMC Medical Informatics and Decision Making, July 2022
DOI 10.1186/s12911-022-01934-2
Pubmed ID
Authors

M. Pishgar, S. Harford, J. Theis, W. Galanter, J. M. Rodríguez-Fernández, L. H Chaisson, Y. Zhang, A. Trotter, K. M. Kochendorfer, A. Boppana, H. Darabi

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X Demographics

The data shown below were collected from the profile of 1 X user 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 26 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 26 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 5 19%
Student > Bachelor 3 12%
Librarian 1 4%
Professor 1 4%
Student > Doctoral Student 1 4%
Other 2 8%
Unknown 13 50%
Readers by discipline Count As %
Computer Science 3 12%
Engineering 3 12%
Business, Management and Accounting 2 8%
Medicine and Dentistry 2 8%
Environmental Science 1 4%
Other 0 0%
Unknown 15 58%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 03 August 2022.
All research outputs
#18,583,054
of 23,016,919 outputs
Outputs from BMC Medical Informatics and Decision Making
#1,583
of 2,008 outputs
Outputs of similar age
#299,776
of 432,115 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#37
of 55 outputs
Altmetric has tracked 23,016,919 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2,008 research outputs from this source. They receive a mean Attention Score of 4.9. This one is in the 9th percentile – i.e., 9% 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 432,115 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 20th percentile – i.e., 20% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 55 others from the same source and published within six weeks on either side of this one. This one is in the 27th percentile – i.e., 27% of its contemporaries scored the same or lower than it.