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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Prediction of adverse cardiac events in emergency department patients with chest pain using machine learning for variable selection
|
|---|---|
| Published in |
BMC Medical Informatics and Decision Making, August 2014
|
| DOI | 10.1186/1472-6947-14-75 |
| Pubmed ID | |
| Authors |
Nan Liu, Zhi Xiong Koh, Junyang Goh, Zhiping Lin, Benjamin Haaland, Boon Ping Ting, Marcus Eng Hock Ong |
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 % |
|---|---|---|
| India | 1 | 50% |
| United Kingdom | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Practitioners (doctors, other healthcare professionals) | 1 | 50% |
| Members of the public | 1 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 176 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | <1% |
| Austria | 1 | <1% |
| Brazil | 1 | <1% |
| Unknown | 173 | 98% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 31 | 18% |
| Student > Ph. D. Student | 23 | 13% |
| Student > Master | 15 | 9% |
| Student > Bachelor | 15 | 9% |
| Other | 12 | 7% |
| Other | 38 | 22% |
| Unknown | 42 | 24% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 54 | 31% |
| Computer Science | 19 | 11% |
| Nursing and Health Professions | 17 | 10% |
| Engineering | 13 | 7% |
| Agricultural and Biological Sciences | 5 | 3% |
| Other | 21 | 12% |
| Unknown | 47 | 27% |
Attention Score in Context
This research output has an Altmetric Attention Score of 4. 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 09 September 2016.
All research outputs
#8,083,151
of 26,017,215 outputs
Outputs from BMC Medical Informatics and Decision Making
#748
of 2,164 outputs
Outputs of similar age
#74,563
of 251,255 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#10
of 31 outputs
Altmetric has tracked 26,017,215 research outputs across all sources so far. This one has received more attention than most of these and is in the 68th percentile.
So far Altmetric has tracked 2,164 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one has gotten more attention than average, scoring higher than 64% 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 251,255 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 69% of its contemporaries.
We're also able to compare this research output to 31 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 67% of its contemporaries.