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American College of Cardiology

Article Metrics

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)
  • High Attention Score compared to outputs of the same age and source (90th percentile)

Mentioned by

twitter
119 tweeters

Citations

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1 Dimensions
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

Twitter Demographics

The data shown below were collected from the profiles of 119 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Attention Score in Context

This research output has an Altmetric Attention Score of 70. 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 10 November 2019.
All research outputs
#252,800
of 13,771,277 outputs
Outputs from JACC: Heart Failure
#64
of 870 outputs
Outputs of similar age
#7,701
of 228,411 outputs
Outputs of similar age from JACC: Heart Failure
#4
of 41 outputs
Altmetric has tracked 13,771,277 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 98th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 870 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 22.8. This one has done particularly well, scoring higher than 92% 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 228,411 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 41 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 90% of its contemporaries.