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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Predicting disease risks from highly imbalanced data using random forest
|
|---|---|
| Published in |
BMC Medical Informatics and Decision Making, July 2011
|
| DOI | 10.1186/1472-6947-11-51 |
| Pubmed ID | |
| Authors |
Mohammed Khalilia, Sounak Chakraborty, Mihail Popescu |
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 % |
|---|---|---|
| India | 1 | 33% |
| United Kingdom | 1 | 33% |
| Unknown | 1 | 33% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 33% |
| Practitioners (doctors, other healthcare professionals) | 1 | 33% |
| Scientists | 1 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 616 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 5 | <1% |
| France | 2 | <1% |
| Indonesia | 1 | <1% |
| Germany | 1 | <1% |
| Iran, Islamic Republic of | 1 | <1% |
| Canada | 1 | <1% |
| Belgium | 1 | <1% |
| Slovenia | 1 | <1% |
| Unknown | 603 | 98% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 134 | 22% |
| Student > Master | 93 | 15% |
| Researcher | 69 | 11% |
| Student > Bachelor | 36 | 6% |
| Student > Doctoral Student | 35 | 6% |
| Other | 87 | 14% |
| Unknown | 162 | 26% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 144 | 23% |
| Engineering | 59 | 10% |
| Medicine and Dentistry | 40 | 6% |
| Agricultural and Biological Sciences | 25 | 4% |
| Business, Management and Accounting | 18 | 3% |
| Other | 126 | 20% |
| Unknown | 204 | 33% |
Attention Score in Context
This research output has an Altmetric Attention Score of 24. 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 May 2023.
All research outputs
#1,422,552
of 23,792,386 outputs
Outputs from BMC Medical Informatics and Decision Making
#60
of 2,024 outputs
Outputs of similar age
#6,191
of 121,418 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#1
of 13 outputs
Altmetric has tracked 23,792,386 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 94th percentile: it's in the top 10% 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 particularly well, scoring higher than 97% 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 121,418 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 94% of its contemporaries.
We're also able to compare this research output to 13 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 99% of its contemporaries.