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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Deploying machine learning with messy, real world data in low- and middle-income countries: Developing a global health use case
|
|---|---|
| Published in |
Frontiers in Big Data, July 2022
|
| DOI | 10.3389/fdata.2022.553673 |
| Pubmed ID | |
| Authors |
Amy Finnegan, David D. Potenziani, Caroline Karutu, Irene Wanyana, Nicholas Matsiko, Cyrus Elahi, Nobert Mijumbi, Richard Stanley, Wayan Vota |
X Demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 6 | 67% |
| Switzerland | 1 | 11% |
| Unknown | 2 | 22% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 7 | 78% |
| Scientists | 1 | 11% |
| Science communicators (journalists, bloggers, editors) | 1 | 11% |
Mendeley readers
The data shown below were compiled from readership statistics for 21 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 21 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Unspecified | 7 | 33% |
| Student > Bachelor | 2 | 10% |
| Researcher | 2 | 10% |
| Other | 1 | 5% |
| Student > Master | 1 | 5% |
| Other | 0 | 0% |
| Unknown | 8 | 38% |
| Readers by discipline | Count | As % |
|---|---|---|
| Unspecified | 7 | 33% |
| Engineering | 2 | 10% |
| Biochemistry, Genetics and Molecular Biology | 1 | 5% |
| Computer Science | 1 | 5% |
| Business, Management and Accounting | 1 | 5% |
| Other | 2 | 10% |
| Unknown | 7 | 33% |
Attention Score in Context
This research output has an Altmetric Attention Score of 6. 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 02 August 2022.
All research outputs
#6,611,244
of 26,473,472 outputs
Outputs from Frontiers in Big Data
#78
of 505 outputs
Outputs of similar age
#114,276
of 439,409 outputs
Outputs of similar age from Frontiers in Big Data
#5
of 30 outputs
Altmetric has tracked 26,473,472 research outputs across all sources so far. Compared to these this one has done well and is in the 75th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 505 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.8. This one has done well, scoring higher than 84% 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 439,409 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 73% of its contemporaries.
We're also able to compare this research output to 30 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 83% of its contemporaries.