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X Demographics
Mendeley readers
Attention Score in Context
| Title |
A machine learning approach for predicting high risk hospitalized patients with COVID-19 SARS-Cov-2
|
|---|---|
| Published in |
BMC Medical Informatics and Decision Making, December 2022
|
| DOI | 10.1186/s12911-022-02076-1 |
| Pubmed ID | |
| Authors |
Alessio Bottrighi, Marzio Pennisi, Annalisa Roveta, Costanza Massarino, Antonella Cassinari, Marta Betti, Tatiana Bolgeo, Marinella Bertolotti, Emanuele Rava, Antonio Maconi |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 27 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 27 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Unspecified | 3 | 11% |
| Lecturer | 3 | 11% |
| Student > Ph. D. Student | 2 | 7% |
| Researcher | 2 | 7% |
| Student > Master | 2 | 7% |
| Other | 1 | 4% |
| Unknown | 14 | 52% |
| Readers by discipline | Count | As % |
|---|---|---|
| Unspecified | 3 | 11% |
| Engineering | 2 | 7% |
| Computer Science | 2 | 7% |
| Business, Management and Accounting | 1 | 4% |
| Medicine and Dentistry | 1 | 4% |
| Other | 1 | 4% |
| Unknown | 17 | 63% |
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 19 March 2023.
All research outputs
#19,006,507
of 23,565,002 outputs
Outputs from BMC Medical Informatics and Decision Making
#1,603
of 2,027 outputs
Outputs of similar age
#302,087
of 439,904 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#32
of 47 outputs
Altmetric has tracked 23,565,002 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2,027 research outputs from this source. They receive a mean Attention Score of 5.0. This one is in the 9th percentile – i.e., 9% 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 439,904 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 20th percentile – i.e., 20% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 47 others from the same source and published within six weeks on either side of this one. This one is in the 23rd percentile – i.e., 23% of its contemporaries scored the same or lower than it.