| Title |
The use of machine learning in the study of suicidal and non-suicidal self-injurious thoughts and behaviors: A systematic review
|
|---|---|
| Published in |
Journal of Affective Disorders, November 2018
|
| DOI | 10.1016/j.jad.2018.11.073 |
| Pubmed ID | |
| Authors |
Taylor A Burke, Brooke A Ammerman, Ross Jacobucci |
X Demographics
The data shown below were collected from the profiles of 6 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 | 3 | 50% |
| Canada | 1 | 17% |
| Germany | 1 | 17% |
| Italy | 1 | 17% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 3 | 50% |
| Scientists | 3 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 234 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 234 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 33 | 14% |
| Researcher | 25 | 11% |
| Student > Bachelor | 23 | 10% |
| Student > Ph. D. Student | 21 | 9% |
| Other | 12 | 5% |
| Other | 44 | 19% |
| Unknown | 76 | 32% |
| Readers by discipline | Count | As % |
|---|---|---|
| Psychology | 44 | 19% |
| Medicine and Dentistry | 26 | 11% |
| Computer Science | 19 | 8% |
| Engineering | 13 | 6% |
| Nursing and Health Professions | 11 | 5% |
| Other | 32 | 14% |
| Unknown | 89 | 38% |
Attention Score in Context
This research output has an Altmetric Attention Score of 24. 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 06 June 2022.
All research outputs
#1,581,303
of 25,385,509 outputs
Outputs from Journal of Affective Disorders
#962
of 10,147 outputs
Outputs of similar age
#32,898
of 356,169 outputs
Outputs of similar age from Journal of Affective Disorders
#25
of 191 outputs
Altmetric has tracked 25,385,509 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 93rd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 10,147 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 13.5. This one has done particularly well, scoring higher than 90% 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 356,169 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 90% of its contemporaries.
We're also able to compare this research output to 191 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 86% of its contemporaries.