| Title |
Development and validation of a pragmatic natural language processing approach to identifying falls in older adults in the emergency department
|
|---|---|
| Published in |
BMC Medical Informatics and Decision Making, July 2019
|
| DOI | 10.1186/s12911-019-0843-7 |
| Pubmed ID | |
| Authors |
Brian W. Patterson, Gwen C. Jacobsohn, Manish N. Shah, Yiqiang Song, Apoorva Maru, Arjun K. Venkatesh, Monica Zhong, Katherine Taylor, Azita G. Hamedani, Eneida A. Mendonça |
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 % |
|---|---|---|
| United States | 2 | 29% |
| Brazil | 1 | 14% |
| United Kingdom | 1 | 14% |
| France | 1 | 14% |
| Unknown | 2 | 29% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 5 | 71% |
| Practitioners (doctors, other healthcare professionals) | 1 | 14% |
| Scientists | 1 | 14% |
Mendeley readers
The data shown below were compiled from readership statistics for 59 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 59 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 9 | 15% |
| Student > Doctoral Student | 7 | 12% |
| Student > Ph. D. Student | 7 | 12% |
| Student > Master | 4 | 7% |
| Professor | 3 | 5% |
| Other | 8 | 14% |
| Unknown | 21 | 36% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 13 | 22% |
| Nursing and Health Professions | 3 | 5% |
| Psychology | 2 | 3% |
| Computer Science | 2 | 3% |
| Sports and Recreations | 2 | 3% |
| Other | 6 | 10% |
| Unknown | 31 | 53% |
Attention Score in Context
This research output has an Altmetric Attention Score of 5. 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 14 September 2019.
All research outputs
#6,448,853
of 23,881,329 outputs
Outputs from BMC Medical Informatics and Decision Making
#574
of 2,030 outputs
Outputs of similar age
#111,377
of 347,829 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#17
of 47 outputs
Altmetric has tracked 23,881,329 research outputs across all sources so far. This one has received more attention than most of these and is in the 72nd percentile.
So far Altmetric has tracked 2,030 research outputs from this source. They receive a mean Attention Score of 4.9. This one has gotten more attention than average, scoring higher than 71% 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 347,829 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 67% of its contemporaries.
We're also able to compare this research output to 47 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 65% of its contemporaries.