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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Evaluation of Pattern Recognition and Feature Extraction Methods in ADHD Prediction
|
|---|---|
| Published in |
Frontiers in Systems Neuroscience, January 2012
|
| DOI | 10.3389/fnsys.2012.00068 |
| Pubmed ID | |
| Authors |
João Ricardo Sato, Marcelo Queiroz Hoexter, André Fujita, Luis Augusto Rohde |
| Abstract |
Attention Deficit/Hyperactivity Disorder (ADHD) is a neurodevelopmental disorder, being one of the most prevalent psychiatric disorders in childhood. The neural substrates associated with this condition, both from structural and functional perspectives, are not yet well established. Recent studies have highlighted the relevance of neuroimaging not only to provide a more solid understanding about the disorder but also for possible clinical support. The ADHD-200 Consortium organized the ADHD-200 global competition making publicly available, hundreds of structural magnetic resonance imaging (MRI) and functional MRI (fMRI) datasets of both ADHD patients and typically developing (TD) controls for research use. In the current study, we evaluate the predictive power of a set of three different feature extraction methods and 10 different pattern recognition methods. The features tested were regional homogeneity (ReHo), amplitude of low frequency fluctuations (ALFF), and independent components analysis maps (resting state networks; RSN). Our findings suggest that the combination ALFF+ReHo maps contain relevant information to discriminate ADHD patients from TD controls, but with limited accuracy. All classifiers provided almost the same performance in this case. In addition, the combination ALFF+ReHo+RSN was relevant in combined vs. inattentive ADHD classification, achieving a score accuracy of 67%. In this latter case, the performances of the classifiers were not equivalent and L2-regularized logistic regression (both in primal and dual space) provided the most accurate predictions. The analysis of brain regions containing most discriminative information suggested that in both classifications (ADHD vs. TD controls and combined vs. inattentive), the relevant information is not confined only to a small set of regions but it is spatially distributed across the whole brain. |
X Demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 125 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 3 | 2% |
| Brazil | 1 | <1% |
| Netherlands | 1 | <1% |
| China | 1 | <1% |
| Singapore | 1 | <1% |
| Unknown | 118 | 94% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 29 | 23% |
| Student > Ph. D. Student | 20 | 16% |
| Student > Master | 15 | 12% |
| Student > Bachelor | 11 | 9% |
| Professor | 7 | 6% |
| Other | 21 | 17% |
| Unknown | 22 | 18% |
| Readers by discipline | Count | As % |
|---|---|---|
| Psychology | 18 | 14% |
| Neuroscience | 17 | 14% |
| Computer Science | 16 | 13% |
| Engineering | 13 | 10% |
| Medicine and Dentistry | 11 | 9% |
| Other | 20 | 16% |
| Unknown | 30 | 24% |
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 24 September 2012.
All research outputs
#23,010,126
of 25,654,806 outputs
Outputs from Frontiers in Systems Neuroscience
#1,299
of 1,410 outputs
Outputs of similar age
#229,709
of 251,300 outputs
Outputs of similar age from Frontiers in Systems Neuroscience
#41
of 51 outputs
Altmetric has tracked 25,654,806 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 1,410 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 11.3. 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 251,300 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 51 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.