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Correction: Machine learning for predicting neurodegenerative diseases in the general older population: a cohort study

Overview of attention for article published in BMC Medical Research Methodology, January 2023
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (80th percentile)
  • High Attention Score compared to outputs of the same age and source (80th percentile)

Mentioned by

news
1 news outlet

Citations

dimensions_citation
2 Dimensions

Readers on

mendeley
2 Mendeley
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Title
Correction: Machine learning for predicting neurodegenerative diseases in the general older population: a cohort study
Published in
BMC Medical Research Methodology, January 2023
DOI 10.1186/s12874-023-01854-3
Pubmed ID
Authors

Gloria A. Aguayo, Lu Zhang, Michel Vaillant, Moses Ngari, Magali Perquin, Valerie Moran, Laetitia Huiart, Rejko Krüger, Francisco Azuaje, Cyril Ferdynus, Guy Fagherazzi

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 2 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 2 100%

Demographic breakdown

Readers by professional status Count As %
Student > Doctoral Student 1 50%
Unknown 1 50%
Readers by discipline Count As %
Psychology 1 50%
Unknown 1 50%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 7. 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 February 2023.
All research outputs
#4,299,207
of 23,344,526 outputs
Outputs from BMC Medical Research Methodology
#705
of 2,060 outputs
Outputs of similar age
#71,675
of 385,081 outputs
Outputs of similar age from BMC Medical Research Methodology
#10
of 47 outputs
Altmetric has tracked 23,344,526 research outputs across all sources so far. Compared to these this one has done well and is in the 80th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,060 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.3. This one has gotten more attention than average, scoring higher than 65% 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 385,081 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 80% of its contemporaries.
We're also able to compare this research output to 47 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 80% of its contemporaries.