| Title |
Blood-Based Biomarkers for Predicting the Risk for Five-Year Incident Coronary Heart Disease in the Framingham Heart Study via Machine Learning
|
|---|---|
| Published in |
Genes, December 2018
|
| DOI | 10.3390/genes9120641 |
| Pubmed ID | |
| Authors |
Meeshanthini V. Dogan, Steven R. H. Beach, Ronald L. Simons, Amaury Lendasse, Brandan Penaluna, Robert A. Philibert |
X Demographics
The data shown below were collected from the profiles of 4 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 25% |
| Germany | 1 | 25% |
| Latvia | 1 | 25% |
| Unknown | 1 | 25% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 3 | 75% |
| Scientists | 1 | 25% |
Mendeley readers
The data shown below were compiled from readership statistics for 71 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 71 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 12 | 17% |
| Student > Ph. D. Student | 8 | 11% |
| Researcher | 6 | 8% |
| Student > Bachelor | 6 | 8% |
| Other | 5 | 7% |
| Other | 11 | 15% |
| Unknown | 23 | 32% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 11 | 15% |
| Biochemistry, Genetics and Molecular Biology | 8 | 11% |
| Medicine and Dentistry | 7 | 10% |
| Nursing and Health Professions | 4 | 6% |
| Engineering | 4 | 6% |
| Other | 14 | 20% |
| Unknown | 23 | 32% |
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 23 December 2018.
All research outputs
#13,398,743
of 23,120,280 outputs
Outputs from Genes
#1,923
of 5,591 outputs
Outputs of similar age
#208,240
of 435,331 outputs
Outputs of similar age from Genes
#69
of 167 outputs
Altmetric has tracked 23,120,280 research outputs across all sources so far. This one is in the 41st percentile – i.e., 41% of other outputs scored the same or lower than it.
So far Altmetric has tracked 5,591 research outputs from this source. They receive a mean Attention Score of 4.6. This one has gotten more attention than average, scoring higher than 63% 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 435,331 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 51% of its contemporaries.
We're also able to compare this research output to 167 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 58% of its contemporaries.