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X Demographics
Mendeley readers
Attention Score in Context
| Title |
A machine learning-based scoring system and ten factors associated with hip fracture occurrence in the elderly
|
|---|---|
| Published in |
BONE, August 2023
|
| DOI | 10.1016/j.bone.2023.116865 |
| Pubmed ID | |
| Authors |
Masaru Uragami, Kozo Matsushita, Yuto Shibata, Shu Takata, Tatsuki Karasugi, Takanao Sueyoshi, Tetsuro Masuda, Takayuki Nakamura, Takuya Tokunaga, Satoshi Hisanaga, Masaki Yugami, Kazuki Sugimoto, Ryuji Yonemitsu, Katsumasa Ideo, Yuko Fukuma, Kosei Takata, Takahiro Arima, Jyunki Kawakami, Kazuya Maeda, Naoto Yoshimura, Hideto Matsunaga, Yuki Kai, Shuntaro Tanimura, Masaki Shimada, Makoto Tateyama, Kana Miyamoto, Ryuta Kubo, Rui Tajiri, Xiao Tian, Fuka Homma, Jun Morinaga, Yoshinori Yamanouchi, Minoru Takebayashi, Naoto Kajitani, Yusuke Uehara, Kumamoto Stop OsteoPorotic Hip Fractures Group, Takeshi Miyamoto |
X Demographics
The data shown below were collected from the profiles of 9 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Japan | 3 | 33% |
| Netherlands | 1 | 11% |
| Unknown | 5 | 56% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 6 | 67% |
| Scientists | 2 | 22% |
| Practitioners (doctors, other healthcare professionals) | 1 | 11% |
Mendeley readers
The data shown below were compiled from readership statistics for 10 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 10 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 1 | 10% |
| Unspecified | 1 | 10% |
| Unknown | 8 | 80% |
| Readers by discipline | Count | As % |
|---|---|---|
| Arts and Humanities | 1 | 10% |
| Unspecified | 1 | 10% |
| Biochemistry, Genetics and Molecular Biology | 1 | 10% |
| Unknown | 7 | 70% |
Attention Score in Context
This research output has an Altmetric Attention Score of 41. 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 23 August 2023.
All research outputs
#1,003,270
of 25,394,764 outputs
Outputs from BONE
#60
of 4,330 outputs
Outputs of similar age
#18,037
of 357,599 outputs
Outputs of similar age from BONE
#1
of 24 outputs
Altmetric has tracked 25,394,764 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 96th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,330 research outputs from this source. They receive a mean Attention Score of 4.9. This one has done particularly well, scoring higher than 98% 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 357,599 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 94% 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.