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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Machine learning predicts mortality based on analysis of ventilation parameters of critically ill patients: multi-centre validation
|
|---|---|
| Published in |
BMC Medical Informatics and Decision Making, May 2021
|
| DOI | 10.1186/s12911-021-01506-w |
| Pubmed ID | |
| Authors |
Behrooz Mamandipoor, Fernando Frutos-Vivar, Oscar Peñuelas, Richard Rezar, Konstantinos Raymondos, Alfonso Muriel, Bin Du, Arnaud W. Thille, Fernando Ríos, Marco González, Lorenzo del-Sorbo, Maria del Carmen Marín, Bruno Valle Pinheiro, Marco Antonio Soares, Nicolas Nin, Salvatore M. Maggiore, Andrew Bersten, Malte Kelm, Raphael Romano Bruno, Pravin Amin, Nahit Cakar, Gee Young Suh, Fekri Abroug, Manuel Jibaja, Dimitros Matamis, Amine Ali Zeggwagh, Yuda Sutherasan, Antonio Anzueto, Bernhard Wernly, Andrés Esteban, Christian Jung, Venet Osmani |
X Demographics
The data shown below were collected from the profiles of 8 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Brazil | 1 | 13% |
| Germany | 1 | 13% |
| Unknown | 6 | 75% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 5 | 63% |
| Scientists | 2 | 25% |
| Practitioners (doctors, other healthcare professionals) | 1 | 13% |
Mendeley readers
The data shown below were compiled from readership statistics for 41 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 41 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 7 | 17% |
| Student > Ph. D. Student | 4 | 10% |
| Other | 3 | 7% |
| Student > Bachelor | 2 | 5% |
| Student > Master | 2 | 5% |
| Other | 4 | 10% |
| Unknown | 19 | 46% |
| Readers by discipline | Count | As % |
|---|---|---|
| Engineering | 5 | 12% |
| Medicine and Dentistry | 5 | 12% |
| Nursing and Health Professions | 3 | 7% |
| Computer Science | 3 | 7% |
| Biochemistry, Genetics and Molecular Biology | 1 | 2% |
| Other | 0 | 0% |
| Unknown | 24 | 59% |
Attention Score in Context
This research output has an Altmetric Attention Score of 7. 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 09 May 2021.
All research outputs
#4,697,807
of 23,308,124 outputs
Outputs from BMC Medical Informatics and Decision Making
#423
of 2,024 outputs
Outputs of similar age
#112,720
of 439,746 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#16
of 60 outputs
Altmetric has tracked 23,308,124 research outputs across all sources so far. Compared to these this one has done well and is in the 79th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,024 research outputs from this source. They receive a mean Attention Score of 4.9. This one has done well, scoring higher than 79% 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 439,746 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 74% of its contemporaries.
We're also able to compare this research output to 60 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.