| Title |
Machine learning techniques in a structural and functional MRI diagnostic approach in schizophrenia: a systematic review
|
|---|---|
| Published in |
Neuropsychiatric Disease and Treatment, June 2019
|
| DOI | 10.2147/ndt.s202418 |
| Pubmed ID | |
| Authors |
Renato de Filippis, Elvira Anna Carbone, Raffaele Gaetano, Antonella Bruni, Valentina Pugliese, Cristina Segura-Garcia, Pasquale De Fazio |
X Demographics
The data shown below were collected from the profiles of 4 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Italy | 1 | 25% |
| United Kingdom | 1 | 25% |
| Singapore | 1 | 25% |
| United States | 1 | 25% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 3 | 75% |
| Scientists | 1 | 25% |
Mendeley readers
The data shown below were compiled from readership statistics for 139 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 139 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 21 | 15% |
| Student > Ph. D. Student | 14 | 10% |
| Researcher | 12 | 9% |
| Student > Bachelor | 11 | 8% |
| Student > Postgraduate | 10 | 7% |
| Other | 18 | 13% |
| Unknown | 53 | 38% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 18 | 13% |
| Neuroscience | 15 | 11% |
| Psychology | 12 | 9% |
| Computer Science | 11 | 8% |
| Engineering | 11 | 8% |
| Other | 13 | 9% |
| Unknown | 59 | 42% |
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 07 June 2021.
All research outputs
#5,450,007
of 25,385,509 outputs
Outputs from Neuropsychiatric Disease and Treatment
#767
of 3,131 outputs
Outputs of similar age
#102,043
of 363,722 outputs
Outputs of similar age from Neuropsychiatric Disease and Treatment
#26
of 97 outputs
Altmetric has tracked 25,385,509 research outputs across all sources so far. Compared to these this one has done well and is in the 75th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 3,131 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.6. This one has gotten more attention than average, scoring higher than 74% 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 363,722 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 71% of its contemporaries.
We're also able to compare this research output to 97 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 73% of its contemporaries.