| Title |
Predicting sample size required for classification performance
|
|---|---|
| Published in |
BMC Medical Informatics and Decision Making, February 2012
|
| DOI | 10.1186/1472-6947-12-8 |
| Pubmed ID | |
| Authors |
Rosa L Figueroa, Qing Zeng-Treitler, Sasikiran Kandula, Long H Ngo |
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 % |
|---|---|---|
| United States | 2 | 25% |
| Japan | 1 | 13% |
| Denmark | 1 | 13% |
| United Kingdom | 1 | 13% |
| India | 1 | 13% |
| Unknown | 2 | 25% |
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 829 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 6 | <1% |
| United Kingdom | 4 | <1% |
| Germany | 3 | <1% |
| Malaysia | 2 | <1% |
| Brazil | 2 | <1% |
| Canada | 2 | <1% |
| Australia | 1 | <1% |
| Sweden | 1 | <1% |
| Switzerland | 1 | <1% |
| Other | 3 | <1% |
| Unknown | 804 | 97% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 165 | 20% |
| Researcher | 138 | 17% |
| Student > Master | 97 | 12% |
| Student > Bachelor | 62 | 7% |
| Other | 46 | 6% |
| Other | 154 | 19% |
| Unknown | 167 | 20% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 126 | 15% |
| Engineering | 116 | 14% |
| Medicine and Dentistry | 94 | 11% |
| Agricultural and Biological Sciences | 53 | 6% |
| Biochemistry, Genetics and Molecular Biology | 33 | 4% |
| Other | 202 | 24% |
| Unknown | 205 | 25% |
Attention Score in Context
This research output has an Altmetric Attention Score of 17. 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 20 February 2024.
All research outputs
#2,023,818
of 24,185,663 outputs
Outputs from BMC Medical Informatics and Decision Making
#112
of 2,066 outputs
Outputs of similar age
#15,850
of 258,018 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#2
of 24 outputs
Altmetric has tracked 24,185,663 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 91st percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,066 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.1. This one has done particularly well, scoring higher than 94% 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 258,018 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 93% of its contemporaries.
We're also able to compare this research output to 24 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 95% of its contemporaries.