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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Comparing machine learning algorithms for predicting COVID-19 mortality
|
|---|---|
| Published in |
BMC Medical Informatics and Decision Making, January 2022
|
| DOI | 10.1186/s12911-021-01742-0 |
| Pubmed ID | |
| Authors |
Khadijeh Moulaei, Mostafa Shanbehzadeh, Zahra Mohammadi-Taghiabad, Hadi Kazemi-Arpanahi |
X Demographics
The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 1 | 33% |
| Comoros | 1 | 33% |
| Unknown | 1 | 33% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 67% |
| Practitioners (doctors, other healthcare professionals) | 1 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 154 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 154 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 11 | 7% |
| Student > Master | 11 | 7% |
| Lecturer | 10 | 6% |
| Student > Bachelor | 10 | 6% |
| Researcher | 9 | 6% |
| Other | 22 | 14% |
| Unknown | 81 | 53% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 20 | 13% |
| Medicine and Dentistry | 11 | 7% |
| Engineering | 8 | 5% |
| Unspecified | 5 | 3% |
| Mathematics | 4 | 3% |
| Other | 22 | 14% |
| Unknown | 84 | 55% |
Attention Score in Context
This research output has an Altmetric Attention Score of 11. 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 February 2023.
All research outputs
#3,037,767
of 23,881,329 outputs
Outputs from BMC Medical Informatics and Decision Making
#224
of 2,030 outputs
Outputs of similar age
#73,948
of 516,954 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#6
of 57 outputs
Altmetric has tracked 23,881,329 research outputs across all sources so far. Compared to these this one has done well and is in the 87th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,030 research outputs from this source. They receive a mean Attention Score of 4.9. This one has done well, scoring higher than 89% 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 516,954 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 85% of its contemporaries.
We're also able to compare this research output to 57 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 91% of its contemporaries.