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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Comparative analysis of machine learning algorithms for multi-syndrome classification of neurodegenerative syndromes
|
|---|---|
| Published in |
Alzheimer's Research & Therapy, May 2022
|
| DOI | 10.1186/s13195-022-00983-z |
| Pubmed ID | |
| Authors |
Leonie Lampe, Sebastian Niehaus, Hans-Jürgen Huppertz, Alberto Merola, Janis Reinelt, Karsten Mueller, Sarah Anderl-Straub, Klaus Fassbender, Klaus Fliessbach, Holger Jahn, Johannes Kornhuber, Martin Lauer, Johannes Prudlo, Anja Schneider, Matthis Synofzik, Adrian Danek, Janine Diehl-Schmid, Markus Otto, Arno Villringer, Karl Egger, Elke Hattingen, Rüdiger Hilker-Roggendorf, Alfons Schnitzler, Martin Südmeyer, Wolfgang Oertel, Jan Kassubek, Günter Höglinger, Matthias L. Schroeter |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
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 52 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 52 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Unspecified | 6 | 12% |
| Researcher | 6 | 12% |
| Student > Bachelor | 4 | 8% |
| Student > Ph. D. Student | 4 | 8% |
| Professor | 3 | 6% |
| Other | 7 | 13% |
| Unknown | 22 | 42% |
| Readers by discipline | Count | As % |
|---|---|---|
| Unspecified | 6 | 12% |
| Psychology | 4 | 8% |
| Medicine and Dentistry | 4 | 8% |
| Neuroscience | 4 | 8% |
| Computer Science | 3 | 6% |
| Other | 8 | 15% |
| Unknown | 23 | 44% |
Attention Score in Context
This research output has an Altmetric Attention Score of 10. 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 13 May 2022.
All research outputs
#3,287,199
of 23,312,088 outputs
Outputs from Alzheimer's Research & Therapy
#873
of 1,268 outputs
Outputs of similar age
#73,749
of 442,928 outputs
Outputs of similar age from Alzheimer's Research & Therapy
#27
of 39 outputs
Altmetric has tracked 23,312,088 research outputs across all sources so far. Compared to these this one has done well and is in the 85th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,268 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 25.9. 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 442,928 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 83% of its contemporaries.
We're also able to compare this research output to 39 others from the same source and published within six weeks on either side of this one. This one is in the 17th percentile – i.e., 17% of its contemporaries scored the same or lower than it.