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Attention Score in Context
| Title |
Regions of interest computed by SVM wrapped method for Alzheimer’s disease examination from segmented MRI
|
|---|---|
| Published in |
Frontiers in Aging Neuroscience, January 2014
|
| DOI | 10.3389/fnagi.2014.00020 |
| Pubmed ID | |
| Authors |
Antonio R. Hidalgo-Muñoz, Javier Ramírez, Juan M. Górriz, Pablo Padilla |
| Abstract |
Accurate identification of the most relevant brain regions linked to Alzheimer's disease (AD) is crucial in order to improve diagnosis techniques and to better understand this neurodegenerative process. For this purpose, statistical classification is suitable. In this work, a novel method based on support vector machine recursive feature elimination (SVM-RFE) is proposed to be applied on segmented brain MRI for detecting the most discriminant AD regions of interest (ROIs). The analyses are performed both on gray and white matter tissues, achieving up to 100% accuracy after classification and outperforming the results obtained by the standard t-test feature selection. The present method, applied on different subject sets, permits automatically determining high-resolution areas surrounding the hippocampal area without needing to divide the brain images according to any common template. |
X Demographics
The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Japan | 1 | 33% |
| Canada | 1 | 33% |
| Spain | 1 | 33% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 2 | 67% |
| Members of the public | 1 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 49 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 49 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 9 | 18% |
| Researcher | 7 | 14% |
| Student > Master | 7 | 14% |
| Student > Postgraduate | 3 | 6% |
| Student > Doctoral Student | 3 | 6% |
| Other | 13 | 27% |
| Unknown | 7 | 14% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 15 | 31% |
| Engineering | 10 | 20% |
| Medicine and Dentistry | 3 | 6% |
| Agricultural and Biological Sciences | 2 | 4% |
| Neuroscience | 2 | 4% |
| Other | 8 | 16% |
| Unknown | 9 | 18% |
Attention Score in Context
This research output has an Altmetric Attention Score of 3. 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 29 January 2020.
All research outputs
#14,499,300
of 24,929,945 outputs
Outputs from Frontiers in Aging Neuroscience
#3,283
of 5,373 outputs
Outputs of similar age
#171,760
of 318,153 outputs
Outputs of similar age from Frontiers in Aging Neuroscience
#9
of 16 outputs
Altmetric has tracked 24,929,945 research outputs across all sources so far. This one is in the 41st percentile – i.e., 41% of other outputs scored the same or lower than it.
So far Altmetric has tracked 5,373 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 14.4. This one is in the 38th percentile – i.e., 38% 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 318,153 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 45th percentile – i.e., 45% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 16 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 50% of its contemporaries.