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Mendeley readers
Attention Score in Context
| Title |
Multivariate Analysis of 18F-DMFP PET Data to Assist the Diagnosis of Parkinsonism
|
|---|---|
| Published in |
Frontiers in Neuroinformatics, March 2017
|
| DOI | 10.3389/fninf.2017.00023 |
| Pubmed ID | |
| Authors |
Fermín Segovia, Juan M. Górriz, Javier Ramírez, Francisco J. Martínez-Murcia, Johannes Levin, Madeleine Schuberth, Matthias Brendel, Axel Rominger, Kai Bötzel, Gaëtan Garraux, Christophe Phillips |
| Abstract |
An early and differential diagnosis of parkinsonian syndromes still remains a challenge mainly due to the similarity of their symptoms during the onset of the disease. Recently, (18)F-Desmethoxyfallypride (DMFP) has been suggested to increase the diagnostic precision as it is an effective radioligand that allows us to analyze post-synaptic dopamine D2/3 receptors. Nevertheless, the analysis of these data is still poorly covered and its use limited. In order to address this challenge, this paper shows a novel model to automatically distinguish idiopathic parkinsonism from non-idiopathic variants using DMFP data. The proposed method is based on a multiple kernel support vector machine and uses the linear version of this classifier to identify some regions of interest: the olfactory bulb, thalamus, and supplementary motor area. We evaluated the proposed model for both, the binary separation of idiopathic and non-idiopathic parkinsonism and the multigroup separation of parkinsonian variants. These systems achieved accuracy rates higher than 70%, outperforming DaTSCAN neuroimages for this purpose. In addition, a system that combined DaTSCAN and DMFP data was assessed. |
X Demographics
The data shown below were collected from the profiles of 5 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Lebanon | 1 | 20% |
| United Kingdom | 1 | 20% |
| Switzerland | 1 | 20% |
| Unknown | 2 | 40% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 4 | 80% |
| Scientists | 1 | 20% |
Mendeley readers
The data shown below were compiled from readership statistics for 37 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 37 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 6 | 16% |
| Student > Ph. D. Student | 5 | 14% |
| Professor | 3 | 8% |
| Student > Doctoral Student | 3 | 8% |
| Other | 2 | 5% |
| Other | 6 | 16% |
| Unknown | 12 | 32% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 8 | 22% |
| Neuroscience | 8 | 22% |
| Agricultural and Biological Sciences | 2 | 5% |
| Engineering | 2 | 5% |
| Computer Science | 2 | 5% |
| Other | 2 | 5% |
| Unknown | 13 | 35% |
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 21 April 2017.
All research outputs
#12,838,700
of 22,962,258 outputs
Outputs from Frontiers in Neuroinformatics
#389
of 751 outputs
Outputs of similar age
#145,657
of 308,948 outputs
Outputs of similar age from Frontiers in Neuroinformatics
#13
of 21 outputs
Altmetric has tracked 22,962,258 research outputs across all sources so far. This one is in the 43rd percentile – i.e., 43% of other outputs scored the same or lower than it.
So far Altmetric has tracked 751 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.3. This one is in the 47th percentile – i.e., 47% 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 308,948 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 52% of its contemporaries.
We're also able to compare this research output to 21 others from the same source and published within six weeks on either side of this one. This one is in the 38th percentile – i.e., 38% of its contemporaries scored the same or lower than it.