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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Learning from Longitudinal Data in Electronic Health Record and Genetic Data to Improve Cardiovascular Event Prediction
|
|---|---|
| Published in |
Scientific Reports, January 2019
|
| DOI | 10.1038/s41598-018-36745-x |
| Pubmed ID | |
| Authors |
Juan Zhao, QiPing Feng, Patrick Wu, Roxana A. Lupu, Russell A. Wilke, Quinn S. Wells, Joshua C. Denny, Wei-Qi Wei |
X Demographics
The data shown below were collected from the profiles of 6 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 | 3 | 50% |
| United Kingdom | 1 | 17% |
| Kenya | 1 | 17% |
| France | 1 | 17% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 5 | 83% |
| Scientists | 1 | 17% |
Mendeley readers
The data shown below were compiled from readership statistics for 314 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 314 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 52 | 17% |
| Researcher | 48 | 15% |
| Student > Master | 35 | 11% |
| Student > Doctoral Student | 27 | 9% |
| Student > Bachelor | 21 | 7% |
| Other | 32 | 10% |
| Unknown | 99 | 32% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 52 | 17% |
| Medicine and Dentistry | 36 | 11% |
| Engineering | 23 | 7% |
| Biochemistry, Genetics and Molecular Biology | 20 | 6% |
| Agricultural and Biological Sciences | 15 | 5% |
| Other | 57 | 18% |
| Unknown | 111 | 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 08 February 2021.
All research outputs
#7,582,957
of 23,124,001 outputs
Outputs from Scientific Reports
#51,732
of 125,005 outputs
Outputs of similar age
#158,781
of 437,870 outputs
Outputs of similar age from Scientific Reports
#1,547
of 3,278 outputs
Altmetric has tracked 23,124,001 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% of other outputs scored the same or lower than it.
So far Altmetric has tracked 125,005 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 18.3. This one has gotten more attention than average, scoring higher than 56% 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 437,870 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 55% of its contemporaries.
We're also able to compare this research output to 3,278 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 50% of its contemporaries.