| Title |
Hip fracture risk assessment: artificial neural network outperforms conditional logistic regression in an age- and sex-matched case control study
|
|---|---|
| Published in |
BMC Musculoskeletal Disorders, July 2013
|
| DOI | 10.1186/1471-2474-14-207 |
| Pubmed ID | |
| Authors |
Wo-Jan Tseng, Li-Wei Hung, Jiann-Shing Shieh, Maysam F Abbod, Jinn Lin |
| Abstract |
Osteoporotic hip fractures with a significant morbidity and excess mortality among the elderly have imposed huge health and economic burdens on societies worldwide. In this age- and sex-matched case control study, we examined the risk factors of hip fractures and assessed the fracture risk by conditional logistic regression (CLR) and ensemble artificial neural network (ANN). The performances of these two classifiers were compared. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Germany | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 85 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 85 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 16 | 19% |
| Student > Master | 9 | 11% |
| Student > Bachelor | 7 | 8% |
| Student > Postgraduate | 6 | 7% |
| Unspecified | 5 | 6% |
| Other | 20 | 24% |
| Unknown | 22 | 26% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 30 | 35% |
| Engineering | 12 | 14% |
| Unspecified | 5 | 6% |
| Nursing and Health Professions | 2 | 2% |
| Biochemistry, Genetics and Molecular Biology | 2 | 2% |
| Other | 7 | 8% |
| Unknown | 27 | 32% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. 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 15 July 2013.
All research outputs
#18,341,711
of 22,714,025 outputs
Outputs from BMC Musculoskeletal Disorders
#3,116
of 4,031 outputs
Outputs of similar age
#145,930
of 194,440 outputs
Outputs of similar age from BMC Musculoskeletal Disorders
#74
of 81 outputs
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So far Altmetric has tracked 4,031 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.0. This one is in the 10th percentile – i.e., 10% of its peers scored the same or lower than it.
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We're also able to compare this research output to 81 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.