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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Predicting SSRI-Resistance: Clinical Features and tagSNPs Prediction Models Based on Support Vector Machine
|
|---|---|
| Published in |
Frontiers in Psychiatry, June 2020
|
| DOI | 10.3389/fpsyt.2020.00493 |
| Pubmed ID | |
| Authors |
Huijie Zhang, Xianglu Li, Jianyue Pang, Xiaofeng Zhao, Suxia Cao, Xinyou Wang, Xingbang Wang, Hengfen Li |
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 % |
|---|---|---|
| Switzerland | 1 | 33% |
| Unknown | 2 | 67% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 3 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 49 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 49 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Bachelor | 10 | 20% |
| Student > Ph. D. Student | 6 | 12% |
| Researcher | 6 | 12% |
| Student > Doctoral Student | 2 | 4% |
| Student > Postgraduate | 2 | 4% |
| Other | 4 | 8% |
| Unknown | 19 | 39% |
| Readers by discipline | Count | As % |
|---|---|---|
| Psychology | 6 | 12% |
| Medicine and Dentistry | 5 | 10% |
| Neuroscience | 5 | 10% |
| Computer Science | 2 | 4% |
| Nursing and Health Professions | 1 | 2% |
| Other | 8 | 16% |
| Unknown | 22 | 45% |
Attention Score in Context
This research output has an Altmetric Attention Score of 9. 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 2024.
All research outputs
#4,455,899
of 26,114,666 outputs
Outputs from Frontiers in Psychiatry
#2,567
of 12,994 outputs
Outputs of similar age
#107,156
of 436,426 outputs
Outputs of similar age from Frontiers in Psychiatry
#101
of 393 outputs
Altmetric has tracked 26,114,666 research outputs across all sources so far. Compared to these this one has done well and is in the 82nd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 12,994 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 11.7. This one has done well, scoring higher than 80% 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 436,426 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 75% of its contemporaries.
We're also able to compare this research output to 393 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 74% of its contemporaries.