| Title |
Prediction of high proliferative index in pituitary macroadenomas using MRI-based radiomics and machine learning
|
|---|---|
| Published in |
Neuroradiology, August 2019
|
| DOI | 10.1007/s00234-019-02266-1 |
| Pubmed ID | |
| Authors |
Lorenzo Ugga, Renato Cuocolo, Domenico Solari, Elia Guadagno, Alessandra D’Amico, Teresa Somma, Paolo Cappabianca, Maria Laura del Basso de Caro, Luigi Maria Cavallo, Arturo Brunetti |
X Demographics
The data shown below were collected from the profiles of 2 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 | 50% |
| United Kingdom | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 50% |
| Practitioners (doctors, other healthcare professionals) | 1 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 58 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 58 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 8 | 14% |
| Student > Ph. D. Student | 8 | 14% |
| Student > Doctoral Student | 7 | 12% |
| Student > Postgraduate | 7 | 12% |
| Other | 5 | 9% |
| Other | 11 | 19% |
| Unknown | 12 | 21% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 25 | 43% |
| Computer Science | 5 | 9% |
| Unspecified | 2 | 3% |
| Engineering | 2 | 3% |
| Business, Management and Accounting | 1 | 2% |
| Other | 5 | 9% |
| Unknown | 18 | 31% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. 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 02 October 2019.
All research outputs
#18,025,888
of 23,153,184 outputs
Outputs from Neuroradiology
#867
of 1,407 outputs
Outputs of similar age
#242,329
of 346,299 outputs
Outputs of similar age from Neuroradiology
#10
of 37 outputs
Altmetric has tracked 23,153,184 research outputs across all sources so far. This one is in the 19th percentile – i.e., 19% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,407 research outputs from this source. They receive a mean Attention Score of 3.8. This one is in the 33rd percentile – i.e., 33% 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 346,299 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 25th percentile – i.e., 25% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 37 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 64% of its contemporaries.