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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Efficient Prediction of Vitamin B Deficiencies via Machine-Learning Using Routine Blood Test Results in Patients With Intense Psychiatric Episode
|
|---|---|
| Published in |
Frontiers in Psychiatry, February 2020
|
| DOI | 10.3389/fpsyt.2019.01029 |
| Pubmed ID | |
| Authors |
Hidetaka Tamune, Jumpei Ukita, Yu Hamamoto, Hiroko Tanaka, Kenji Narushima, Naoki Yamamoto |
X Demographics
The data shown below were collected from the profiles of 9 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Japan | 2 | 22% |
| Switzerland | 1 | 11% |
| Unknown | 6 | 67% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 7 | 78% |
| Scientists | 1 | 11% |
| Practitioners (doctors, other healthcare professionals) | 1 | 11% |
Mendeley readers
The data shown below were compiled from readership statistics for 37 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 37 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 7 | 19% |
| Student > Ph. D. Student | 7 | 19% |
| Student > Bachelor | 4 | 11% |
| Student > Master | 3 | 8% |
| Student > Doctoral Student | 2 | 5% |
| Other | 5 | 14% |
| Unknown | 9 | 24% |
| Readers by discipline | Count | As % |
|---|---|---|
| Psychology | 6 | 16% |
| Medicine and Dentistry | 6 | 16% |
| Computer Science | 4 | 11% |
| Neuroscience | 3 | 8% |
| Biochemistry, Genetics and Molecular Biology | 2 | 5% |
| Other | 5 | 14% |
| Unknown | 11 | 30% |
Attention Score in Context
This research output has an Altmetric Attention Score of 6. 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 10 April 2020.
All research outputs
#6,730,135
of 26,099,501 outputs
Outputs from Frontiers in Psychiatry
#3,206
of 12,986 outputs
Outputs of similar age
#118,085
of 386,881 outputs
Outputs of similar age from Frontiers in Psychiatry
#112
of 353 outputs
Altmetric has tracked 26,099,501 research outputs across all sources so far. This one has received more attention than most of these and is in the 74th percentile.
So far Altmetric has tracked 12,986 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 75% 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 386,881 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 69% of its contemporaries.
We're also able to compare this research output to 353 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 67% of its contemporaries.