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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Stratifying patients using fast multiple kernel learning framework: case studies of Alzheimer’s disease and cancers
|
|---|---|
| Published in |
BMC Medical Informatics and Decision Making, June 2020
|
| DOI | 10.1186/s12911-020-01140-y |
| Pubmed ID | |
| Authors |
Thanh-Trung Giang, Thanh-Phuong Nguyen, Dang-Hung Tran |
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 68 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 68 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Bachelor | 7 | 10% |
| Student > Ph. D. Student | 6 | 9% |
| Student > Master | 6 | 9% |
| Researcher | 4 | 6% |
| Professor > Associate Professor | 4 | 6% |
| Other | 13 | 19% |
| Unknown | 28 | 41% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 13 | 19% |
| Unspecified | 4 | 6% |
| Biochemistry, Genetics and Molecular Biology | 3 | 4% |
| Computer Science | 3 | 4% |
| Pharmacology, Toxicology and Pharmaceutical Science | 3 | 4% |
| Other | 8 | 12% |
| Unknown | 34 | 50% |
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 26 June 2020.
All research outputs
#3,190,974
of 23,215,490 outputs
Outputs from BMC Medical Informatics and Decision Making
#267
of 2,019 outputs
Outputs of similar age
#78,806
of 372,009 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#7
of 51 outputs
Altmetric has tracked 23,215,490 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 2,019 research outputs from this source. They receive a mean Attention Score of 4.9. 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 372,009 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 78% of its contemporaries.
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 has done well, scoring higher than 86% of its contemporaries.