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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Using artificial intelligence to reduce diagnostic workload without compromising detection of urinary tract infections
|
|---|---|
| Published in |
BMC Medical Informatics and Decision Making, August 2019
|
| DOI | 10.1186/s12911-019-0878-9 |
| Pubmed ID | |
| Authors |
Ross J. Burton, Mahableshwar Albur, Matthias Eberl, Simone M. Cuff |
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 Kingdom | 4 | 50% |
| United States | 1 | 13% |
| Unknown | 3 | 38% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 4 | 50% |
| Scientists | 4 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 174 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 174 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 20 | 11% |
| Unspecified | 17 | 10% |
| Student > Ph. D. Student | 17 | 10% |
| Student > Master | 17 | 10% |
| Student > Bachelor | 10 | 6% |
| Other | 28 | 16% |
| Unknown | 65 | 37% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 19 | 11% |
| Unspecified | 17 | 10% |
| Computer Science | 11 | 6% |
| Engineering | 10 | 6% |
| Biochemistry, Genetics and Molecular Biology | 8 | 5% |
| Other | 34 | 20% |
| Unknown | 75 | 43% |
Attention Score in Context
This research output has an Altmetric Attention Score of 7. 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 October 2019.
All research outputs
#5,167,532
of 24,833,726 outputs
Outputs from BMC Medical Informatics and Decision Making
#461
of 2,116 outputs
Outputs of similar age
#94,240
of 347,088 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#14
of 41 outputs
Altmetric has tracked 24,833,726 research outputs across all sources so far. Compared to these this one has done well and is in the 79th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,116 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.3. This one has done well, scoring higher than 78% 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 347,088 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 72% of its contemporaries.
We're also able to compare this research output to 41 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 68% of its contemporaries.