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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Comparing different supervised machine learning algorithms for disease prediction
|
|---|---|
| Published in |
BMC Medical Informatics and Decision Making, December 2019
|
| DOI | 10.1186/s12911-019-1004-8 |
| Pubmed ID | |
| Authors |
Shahadat Uddin, Arif Khan, Md Ekramul Hossain, Mohammad Ali Moni |
X Demographics
The data shown below were collected from the profiles of 7 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Mexico | 1 | 14% |
| Sweden | 1 | 14% |
| South Africa | 1 | 14% |
| United Kingdom | 1 | 14% |
| Unknown | 3 | 43% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 7 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 1,632 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1632 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 159 | 10% |
| Student > Ph. D. Student | 141 | 9% |
| Student > Bachelor | 126 | 8% |
| Researcher | 83 | 5% |
| Lecturer | 54 | 3% |
| Other | 200 | 12% |
| Unknown | 869 | 53% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 233 | 14% |
| Engineering | 139 | 9% |
| Medicine and Dentistry | 52 | 3% |
| Biochemistry, Genetics and Molecular Biology | 47 | 3% |
| Unspecified | 42 | 3% |
| Other | 216 | 13% |
| Unknown | 903 | 55% |
Attention Score in Context
This research output has an Altmetric Attention Score of 13. 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 08 February 2024.
All research outputs
#2,803,100
of 25,761,363 outputs
Outputs from BMC Medical Informatics and Decision Making
#181
of 2,158 outputs
Outputs of similar age
#65,735
of 481,712 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#9
of 69 outputs
Altmetric has tracked 25,761,363 research outputs across all sources so far. Compared to these this one has done well and is in the 89th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,158 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one has done particularly well, scoring higher than 91% 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 481,712 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 86% of its contemporaries.
We're also able to compare this research output to 69 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 86% of its contemporaries.