| Title |
Predicting patient-reported outcomes following hip and knee replacement surgery using supervised machine learning
|
|---|---|
| Published in |
BMC Medical Informatics and Decision Making, January 2019
|
| DOI | 10.1186/s12911-018-0731-6 |
| Pubmed ID | |
| Authors |
Manuel Huber, Christoph Kurz, Reiner Leidl |
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 Kingdom | 3 | 38% |
| Australia | 1 | 13% |
| United States | 1 | 13% |
| Unknown | 3 | 38% |
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 203 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 203 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Unspecified | 26 | 13% |
| Student > Ph. D. Student | 24 | 12% |
| Researcher | 23 | 11% |
| Student > Master | 21 | 10% |
| Student > Bachelor | 14 | 7% |
| Other | 30 | 15% |
| Unknown | 65 | 32% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 40 | 20% |
| Unspecified | 26 | 13% |
| Engineering | 14 | 7% |
| Nursing and Health Professions | 12 | 6% |
| Computer Science | 10 | 5% |
| Other | 28 | 14% |
| Unknown | 73 | 36% |
Attention Score in Context
This research output has an Altmetric Attention Score of 15. 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 12 March 2024.
All research outputs
#2,481,454
of 25,543,275 outputs
Outputs from BMC Medical Informatics and Decision Making
#150
of 2,149 outputs
Outputs of similar age
#56,048
of 447,589 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#7
of 52 outputs
Altmetric has tracked 25,543,275 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 90th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,149 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 93% 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 447,589 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 87% of its contemporaries.
We're also able to compare this research output to 52 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 88% of its contemporaries.