↓ Skip to main content

Genetic algorithm with logistic regression for prediction of progression to Alzheimer's disease

Overview of attention for article published in BMC Bioinformatics, January 2014
Altmetric Badge

About this Attention Score

  • Average Attention Score compared to outputs of the same age

Mentioned by

twitter
2 tweeters
facebook
1 Facebook page

Citations

dimensions_citation
34 Dimensions

Readers on

mendeley
68 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Genetic algorithm with logistic regression for prediction of progression to Alzheimer's disease
Published in
BMC Bioinformatics, January 2014
DOI 10.1186/1471-2105-15-s16-s11
Pubmed ID
Authors

Piers Johnson, Luke Vandewater, William Wilson, Paul Maruff, Greg Savage, Petra Graham, Lance S Macaulay, Kathryn A Ellis, Cassandra Szoeke, Ralph N Martins, Christopher C Rowe, Colin L Masters, David Ames, Ping Zhang

Abstract

Assessment of risk and early diagnosis of Alzheimer's disease (AD) is a key to its prevention or slowing the progression of the disease. Previous research on risk factors for AD typically utilizes statistical comparison tests or stepwise selection with regression models. Outcomes of these methods tend to emphasize single risk factors rather than a combination of risk factors. However, a combination of factors, rather than any one alone, is likely to affect disease development. Genetic algorithms (GA) can be useful and efficient for searching a combination of variables for the best achievement (eg. accuracy of diagnosis), especially when the search space is large, complex or poorly understood, as in the case in prediction of AD development.

Twitter Demographics

The data shown below were collected from the profiles of 2 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 68 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 1 1%
Australia 1 1%
Unknown 66 97%

Demographic breakdown

Readers by professional status Count As %
Researcher 15 22%
Student > Ph. D. Student 14 21%
Student > Master 14 21%
Student > Bachelor 6 9%
Student > Postgraduate 3 4%
Other 7 10%
Unknown 9 13%
Readers by discipline Count As %
Computer Science 10 15%
Psychology 10 15%
Agricultural and Biological Sciences 7 10%
Engineering 6 9%
Biochemistry, Genetics and Molecular Biology 5 7%
Other 16 24%
Unknown 14 21%

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 14 May 2015.
All research outputs
#7,762,557
of 12,373,386 outputs
Outputs from BMC Bioinformatics
#3,171
of 4,588 outputs
Outputs of similar age
#118,769
of 220,919 outputs
Outputs of similar age from BMC Bioinformatics
#8
of 8 outputs
Altmetric has tracked 12,373,386 research outputs across all sources so far. This one is in the 23rd percentile – i.e., 23% of other outputs scored the same or lower than it.
So far Altmetric has tracked 4,588 research outputs from this source. They receive a mean Attention Score of 4.9. This one is in the 21st percentile – i.e., 21% 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 220,919 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 36th percentile – i.e., 36% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 8 others from the same source and published within six weeks on either side of this one.