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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Prediction of amyloid PET positivity via machine learning algorithms trained with EDTA-based blood amyloid-β oligomerization data
|
|---|---|
| Published in |
BMC Medical Informatics and Decision Making, November 2022
|
| DOI | 10.1186/s12911-022-02024-z |
| Pubmed ID | |
| Authors |
Young Chul Youn, Hye Ryoun Kim, Hae-Won Shin, Hae-Bong Jeong, Sang-Won Han, Jung-Min Pyun, Nayoung Ryoo, Young Ho Park, SangYun Kim |
X Demographics
The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 2 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 11 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 11 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Unspecified | 2 | 18% |
| Researcher | 2 | 18% |
| Librarian | 1 | 9% |
| Lecturer | 1 | 9% |
| Student > Master | 1 | 9% |
| Other | 0 | 0% |
| Unknown | 4 | 36% |
| Readers by discipline | Count | As % |
|---|---|---|
| Unspecified | 2 | 18% |
| Medicine and Dentistry | 2 | 18% |
| Neuroscience | 1 | 9% |
| Nursing and Health Professions | 1 | 9% |
| Unknown | 5 | 45% |
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 11 November 2022.
All research outputs
#3,465,310
of 24,796,076 outputs
Outputs from BMC Medical Informatics and Decision Making
#274
of 2,115 outputs
Outputs of similar age
#68,964
of 435,489 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#6
of 38 outputs
Altmetric has tracked 24,796,076 research outputs across all sources so far. Compared to these this one has done well and is in the 86th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,115 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.3. This one has done well, scoring higher than 86% of its peers.
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 435,489 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 84% of its contemporaries.
We're also able to compare this research output to 38 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 86% of its contemporaries.