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A novel approach for heart disease prediction using strength scores with significant predictors

Overview of attention for article published in BMC Medical Informatics and Decision Making, June 2021
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Mentioned by

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1 X user

Citations

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42 Dimensions

Readers on

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70 Mendeley
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Title
A novel approach for heart disease prediction using strength scores with significant predictors
Published in
BMC Medical Informatics and Decision Making, June 2021
DOI 10.1186/s12911-021-01527-5
Pubmed ID
Authors

Armin Yazdani, Kasturi Dewi Varathan, Yin Kia Chiam, Asad Waqar Malik, Wan Azman Wan Ahmad

X Demographics

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 70 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 70 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 5 7%
Student > Master 5 7%
Researcher 5 7%
Student > Ph. D. Student 5 7%
Unspecified 4 6%
Other 4 6%
Unknown 42 60%
Readers by discipline Count As %
Computer Science 13 19%
Unspecified 4 6%
Nursing and Health Professions 2 3%
Design 2 3%
Neuroscience 2 3%
Other 3 4%
Unknown 44 63%
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 25 June 2021.
All research outputs
#20,707,815
of 23,308,124 outputs
Outputs from BMC Medical Informatics and Decision Making
#1,832
of 2,024 outputs
Outputs of similar age
#365,616
of 444,798 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#52
of 62 outputs
Altmetric has tracked 23,308,124 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% 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 1st percentile – i.e., 1% 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 444,798 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% 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 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.