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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Distinguishing Parkinson's disease from atypical parkinsonian syndromes using PET data and a computer system based on support vector machines and Bayesian networks
|
|---|---|
| Published in |
Frontiers in Computational Neuroscience, November 2015
|
| DOI | 10.3389/fncom.2015.00137 |
| Pubmed ID | |
| Authors |
Fermín Segovia, Ignacio A. Illán, Juan M. Górriz, Javier Ramírez, Axel Rominger, Johannes Levin |
| Abstract |
Differentiating between Parkinson's disease (PD) and atypical parkinsonian syndromes (APS) is still a challenge, specially at early stages when the patients show similar symptoms. During last years, several computer systems have been proposed in order to improve the diagnosis of PD, but their accuracy is still limited. In this work we demonstrate a full automatic computer system to assist the diagnosis of PD using (18)F-DMFP PET data. First, a few regions of interest are selected by means of a two-sample t-test. The accuracy of the selected regions to separate PD from APS patients is then computed using a support vector machine classifier. The accuracy values are finally used to train a Bayesian network that can be used to predict the class of new unseen data. This methodology was evaluated using a database with 87 neuroimages, achieving accuracy rates over 78%. A fair comparison with other similar approaches is also provided. |
X Demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Switzerland | 1 | 33% |
| Unknown | 2 | 67% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 67% |
| Scientists | 1 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 41 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 2% |
| Unknown | 40 | 98% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 6 | 15% |
| Student > Master | 6 | 15% |
| Researcher | 5 | 12% |
| Other | 5 | 12% |
| Professor > Associate Professor | 3 | 7% |
| Other | 7 | 17% |
| Unknown | 9 | 22% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 8 | 20% |
| Engineering | 7 | 17% |
| Agricultural and Biological Sciences | 5 | 12% |
| Neuroscience | 5 | 12% |
| Computer Science | 3 | 7% |
| Other | 3 | 7% |
| Unknown | 10 | 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 11 November 2015.
All research outputs
#15,349,796
of 22,832,057 outputs
Outputs from Frontiers in Computational Neuroscience
#873
of 1,343 outputs
Outputs of similar age
#166,996
of 285,414 outputs
Outputs of similar age from Frontiers in Computational Neuroscience
#26
of 36 outputs
Altmetric has tracked 22,832,057 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,343 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.2. This one is in the 28th percentile – i.e., 28% 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 285,414 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 32nd percentile – i.e., 32% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 36 others from the same source and published within six weeks on either side of this one. This one is in the 22nd percentile – i.e., 22% of its contemporaries scored the same or lower than it.