| Title |
Exploratory analysis of machine learning approaches for surveillance of Zika‐associated birth defects
|
|---|---|
| Published in |
Birth Defects Research, August 2020
|
| DOI | 10.1002/bdr2.1767 |
| Pubmed ID | |
| Authors |
Richard Lusk, John Zimmerman, Kelley VanMaldeghem, Suzanna Kim, Nicole M. Roth, James Lavinder, Anna Fulton, Meghan Raycraft, Sascha R. Ellington, Romeo R. Galang |
X Demographics
The data shown below were collected from the profiles of 8 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 | 6 | 75% |
| Unknown | 2 | 25% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 4 | 50% |
| Practitioners (doctors, other healthcare professionals) | 3 | 38% |
| Science communicators (journalists, bloggers, editors) | 1 | 13% |
Mendeley readers
The data shown below were compiled from readership statistics for 33 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 33 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 4 | 12% |
| Student > Bachelor | 4 | 12% |
| Student > Ph. D. Student | 3 | 9% |
| Student > Master | 2 | 6% |
| Student > Doctoral Student | 1 | 3% |
| Other | 0 | 0% |
| Unknown | 19 | 58% |
| Readers by discipline | Count | As % |
|---|---|---|
| Nursing and Health Professions | 3 | 9% |
| Agricultural and Biological Sciences | 2 | 6% |
| Medicine and Dentistry | 2 | 6% |
| Computer Science | 2 | 6% |
| Environmental Science | 1 | 3% |
| Other | 2 | 6% |
| Unknown | 21 | 64% |
Attention Score in Context
This research output has an Altmetric Attention Score of 118. 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 01 June 2021.
All research outputs
#355,290
of 25,387,668 outputs
Outputs from Birth Defects Research
#43
of 561 outputs
Outputs of similar age
#10,963
of 425,847 outputs
Outputs of similar age from Birth Defects Research
#1
of 34 outputs
Altmetric has tracked 25,387,668 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 98th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 561 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 36.8. This one has done particularly well, scoring higher than 92% 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 425,847 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 97% of its contemporaries.
We're also able to compare this research output to 34 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 97% of its contemporaries.