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American College of Cardiology

Machine Learning Prediction of Mortality and Hospitalization in Heart Failure With Preserved Ejection Fraction

Overview of attention for article published in JACC: Heart Failure, October 2019
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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)
  • Good Attention Score compared to outputs of the same age and source (78th percentile)

Mentioned by

twitter
121 X users
facebook
2 Facebook pages

Citations

dimensions_citation
174 Dimensions

Readers on

mendeley
226 Mendeley
Title
Machine Learning Prediction of Mortality and Hospitalization in Heart Failure With Preserved Ejection Fraction
Published in
JACC: Heart Failure, October 2019
DOI 10.1016/j.jchf.2019.06.013
Pubmed ID
Authors

Suveen Angraal, Bobak J Mortazavi, Aakriti Gupta, Rohan Khera, Tariq Ahmad, Nihar R Desai, Daniel L Jacoby, Frederick A Masoudi, John A Spertus, Harlan M Krumholz

X Demographics

X Demographics

The data shown below were collected from the profiles of 121 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 226 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 226 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 29 13%
Student > Master 21 9%
Student > Ph. D. Student 18 8%
Other 17 8%
Student > Bachelor 15 7%
Other 42 19%
Unknown 84 37%
Readers by discipline Count As %
Medicine and Dentistry 51 23%
Computer Science 21 9%
Engineering 14 6%
Nursing and Health Professions 8 4%
Biochemistry, Genetics and Molecular Biology 7 3%
Other 22 10%
Unknown 103 46%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 69. 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 07 April 2022.
All research outputs
#622,598
of 25,587,485 outputs
Outputs from JACC: Heart Failure
#166
of 1,600 outputs
Outputs of similar age
#13,606
of 367,021 outputs
Outputs of similar age from JACC: Heart Failure
#8
of 32 outputs
Altmetric has tracked 25,587,485 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 97th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,600 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 30.3. This one has done well, scoring higher than 89% 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 367,021 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 32 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 78% of its contemporaries.