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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Using artificial intelligence to identify patients with migraine and associated symptoms and conditions within electronic health records
|
|---|---|
| Published in |
BMC Medical Informatics and Decision Making, July 2023
|
| DOI | 10.1186/s12911-023-02190-8 |
| Pubmed ID | |
| Authors |
Daniel Riskin, Roger Cady, Anand Shroff, Nada A. Hindiyeh, Timothy Smith, Steven Kymes |
X Demographics
The data shown below were collected from the profiles of 3 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 | 2 | 67% |
| Unknown | 1 | 33% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 67% |
| Practitioners (doctors, other healthcare professionals) | 1 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 34 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 34 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Unspecified | 5 | 15% |
| Lecturer | 1 | 3% |
| Student > Doctoral Student | 1 | 3% |
| Student > Ph. D. Student | 1 | 3% |
| Student > Master | 1 | 3% |
| Other | 2 | 6% |
| Unknown | 23 | 68% |
| Readers by discipline | Count | As % |
|---|---|---|
| Unspecified | 5 | 15% |
| Engineering | 2 | 6% |
| Agricultural and Biological Sciences | 1 | 3% |
| Arts and Humanities | 1 | 3% |
| Neuroscience | 1 | 3% |
| Other | 1 | 3% |
| Unknown | 23 | 68% |
Attention Score in Context
This research output has an Altmetric Attention Score of 239. 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 August 2023.
All research outputs
#153,213
of 24,998,746 outputs
Outputs from BMC Medical Informatics and Decision Making
#2
of 2,120 outputs
Outputs of similar age
#3,166
of 349,073 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#1
of 20 outputs
Altmetric has tracked 24,998,746 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 99th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,120 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 particularly well, scoring higher than 99% 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 349,073 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 99% of its contemporaries.
We're also able to compare this research output to 20 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 99% of its contemporaries.