| Title |
Identifying clinically important COPD sub-types using data-driven approaches in primary care population based electronic health records
|
|---|---|
| Published in |
BMC Medical Informatics and Decision Making, April 2019
|
| DOI | 10.1186/s12911-019-0805-0 |
| Pubmed ID | |
| Authors |
Maria Pikoula, Jennifer Kathleen Quint, Francis Nissen, Harry Hemingway, Liam Smeeth, Spiros Denaxas |
X Demographics
The data shown below were collected from the profiles of 73 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 | 32 | 44% |
| Spain | 6 | 8% |
| Australia | 4 | 5% |
| Canada | 4 | 5% |
| United States | 2 | 3% |
| Ecuador | 1 | 1% |
| Pakistan | 1 | 1% |
| Brazil | 1 | 1% |
| Philippines | 1 | 1% |
| Other | 3 | 4% |
| Unknown | 18 | 25% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 47 | 64% |
| Scientists | 18 | 25% |
| Practitioners (doctors, other healthcare professionals) | 7 | 10% |
| Science communicators (journalists, bloggers, editors) | 1 | 1% |
Mendeley readers
The data shown below were compiled from readership statistics for 187 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 187 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 37 | 20% |
| Researcher | 24 | 13% |
| Student > Master | 16 | 9% |
| Student > Bachelor | 12 | 6% |
| Other | 9 | 5% |
| Other | 29 | 16% |
| Unknown | 60 | 32% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 42 | 22% |
| Nursing and Health Professions | 16 | 9% |
| Psychology | 10 | 5% |
| Computer Science | 10 | 5% |
| Agricultural and Biological Sciences | 7 | 4% |
| Other | 31 | 17% |
| Unknown | 71 | 38% |
Attention Score in Context
This research output has an Altmetric Attention Score of 46. 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 24 March 2020.
All research outputs
#926,842
of 25,918,104 outputs
Outputs from BMC Medical Informatics and Decision Making
#27
of 2,162 outputs
Outputs of similar age
#20,799
of 367,330 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#1
of 49 outputs
Altmetric has tracked 25,918,104 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 96th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,162 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one has done particularly well, scoring higher than 98% 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 367,330 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 94% of its contemporaries.
We're also able to compare this research output to 49 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.