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Machine learning methodologies versus cardiovascular risk scores, in predicting disease risk

Overview of attention for article published in BMC Medical Research Methodology, December 2018
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (67th percentile)
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

twitter
6 tweeters

Citations

dimensions_citation
61 Dimensions

Readers on

mendeley
170 Mendeley
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Title
Machine learning methodologies versus cardiovascular risk scores, in predicting disease risk
Published in
BMC Medical Research Methodology, December 2018
DOI 10.1186/s12874-018-0644-1
Pubmed ID
Authors

Alexandros C. Dimopoulos, Mara Nikolaidou, Francisco Félix Caballero, Worrawat Engchuan, Albert Sanchez-Niubo, Holger Arndt, José Luis Ayuso-Mateos, Josep Maria Haro, Somnath Chatterji, Ekavi N. Georgousopoulou, Christos Pitsavos, Demosthenes B. Panagiotakos

Twitter Demographics

Twitter Demographics

The data shown below were collected from the profiles of 6 tweeters 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 170 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 170 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 21 12%
Student > Master 20 12%
Researcher 18 11%
Student > Bachelor 16 9%
Student > Doctoral Student 9 5%
Other 34 20%
Unknown 52 31%
Readers by discipline Count As %
Medicine and Dentistry 24 14%
Computer Science 23 14%
Engineering 18 11%
Unspecified 9 5%
Nursing and Health Professions 7 4%
Other 28 16%
Unknown 61 36%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 18 June 2019.
All research outputs
#6,969,786
of 23,305,591 outputs
Outputs from BMC Medical Research Methodology
#1,031
of 2,054 outputs
Outputs of similar age
#141,829
of 438,629 outputs
Outputs of similar age from BMC Medical Research Methodology
#48
of 70 outputs
Altmetric has tracked 23,305,591 research outputs across all sources so far. This one has received more attention than most of these and is in the 69th percentile.
So far Altmetric has tracked 2,054 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.3. This one is in the 49th percentile – i.e., 49% 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 438,629 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 67% of its contemporaries.
We're also able to compare this research output to 70 others from the same source and published within six weeks on either side of this one. This one is in the 32nd percentile – i.e., 32% of its contemporaries scored the same or lower than it.