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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Integration and Validation of a Natural Language Processing Machine Learning Suicide Risk Prediction Model Based on Open-Ended Interview Language in the Emergency Department
|
|---|---|
| Published in |
Frontiers in Digital Health, February 2022
|
| DOI | 10.3389/fdgth.2022.818705 |
| Pubmed ID | |
| Authors |
Joshua Cohen, Jennifer Wright-Berryman, Lesley Rohlfs, Douglas Trocinski, LaMonica Daniel, Thomas W. Klatt |
X Demographics
The data shown below were collected from the profiles of 5 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 | 1 | 20% |
| France | 1 | 20% |
| Switzerland | 1 | 20% |
| Unknown | 2 | 40% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 5 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 41 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 41 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 6 | 15% |
| Unspecified | 3 | 7% |
| Student > Bachelor | 3 | 7% |
| Student > Ph. D. Student | 2 | 5% |
| Student > Master | 2 | 5% |
| Other | 1 | 2% |
| Unknown | 24 | 59% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 4 | 10% |
| Unspecified | 3 | 7% |
| Psychology | 3 | 7% |
| Mathematics | 1 | 2% |
| Computer Science | 1 | 2% |
| Other | 5 | 12% |
| Unknown | 24 | 59% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. 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 27 February 2022.
All research outputs
#14,912,812
of 24,987,787 outputs
Outputs from Frontiers in Digital Health
#416
of 768 outputs
Outputs of similar age
#233,134
of 515,237 outputs
Outputs of similar age from Frontiers in Digital Health
#35
of 62 outputs
Altmetric has tracked 24,987,787 research outputs across all sources so far. This one is in the 38th percentile – i.e., 38% of other outputs scored the same or lower than it.
So far Altmetric has tracked 768 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.5. This one is in the 43rd percentile – i.e., 43% of its peers scored the same or lower than it.
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 515,237 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 52% of its contemporaries.
We're also able to compare this research output to 62 others from the same source and published within six weeks on either side of this one. This one is in the 38th percentile – i.e., 38% of its contemporaries scored the same or lower than it.