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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Application of machine learning models based on decision trees in classifying the factors affecting mortality of COVID-19 patients in Hamadan, Iran
|
|---|---|
| Published in |
BMC Medical Informatics and Decision Making, July 2022
|
| DOI | 10.1186/s12911-022-01939-x |
| Pubmed ID | |
| Authors |
Samad Moslehi, Niloofar Rabiei, Ali Reza Soltanian, Mojgan Mamani |
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 % |
|---|---|---|
| South Africa | 1 | 50% |
| United States | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 37 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 37 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 6 | 16% |
| Student > Bachelor | 3 | 8% |
| Researcher | 3 | 8% |
| Lecturer | 1 | 3% |
| Student > Doctoral Student | 1 | 3% |
| Other | 5 | 14% |
| Unknown | 18 | 49% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 7 | 19% |
| Engineering | 3 | 8% |
| Medicine and Dentistry | 2 | 5% |
| Nursing and Health Professions | 2 | 5% |
| Pharmacology, Toxicology and Pharmaceutical Science | 1 | 3% |
| Other | 4 | 11% |
| Unknown | 18 | 49% |
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 24 July 2022.
All research outputs
#19,416,201
of 23,885,338 outputs
Outputs from BMC Medical Informatics and Decision Making
#1,615
of 2,048 outputs
Outputs of similar age
#305,864
of 418,988 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#37
of 55 outputs
Altmetric has tracked 23,885,338 research outputs across all sources so far. This one is in the 10th percentile – i.e., 10% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2,048 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 418,988 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 16th percentile – i.e., 16% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 55 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.