| Title |
Salivary metabolomics with alternative decision tree-based machine learning methods for breast cancer discrimination
|
|---|---|
| Published in |
Breast Cancer Research and Treatment, July 2019
|
| DOI | 10.1007/s10549-019-05330-9 |
| Pubmed ID | |
| Authors |
Takeshi Murata, Takako Yanagisawa, Toshiaki Kurihara, Miku Kaneko, Sana Ota, Ayame Enomoto, Masaru Tomita, Masahiro Sugimoto, Makoto Sunamura, Tetsu Hayashida, Yuko Kitagawa, Hiromitsu Jinno |
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 % |
|---|---|---|
| United States | 1 | 50% |
| Unknown | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Science communicators (journalists, bloggers, editors) | 1 | 50% |
| Members of the public | 1 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 102 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 102 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Bachelor | 15 | 15% |
| Student > Ph. D. Student | 13 | 13% |
| Researcher | 10 | 10% |
| Student > Master | 10 | 10% |
| Student > Doctoral Student | 8 | 8% |
| Other | 17 | 17% |
| Unknown | 29 | 28% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 22 | 22% |
| Biochemistry, Genetics and Molecular Biology | 10 | 10% |
| Pharmacology, Toxicology and Pharmaceutical Science | 6 | 6% |
| Computer Science | 5 | 5% |
| Engineering | 5 | 5% |
| Other | 21 | 21% |
| Unknown | 33 | 32% |
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 07 March 2024.
All research outputs
#8,046,266
of 25,605,018 outputs
Outputs from Breast Cancer Research and Treatment
#1,698
of 4,991 outputs
Outputs of similar age
#134,765
of 361,717 outputs
Outputs of similar age from Breast Cancer Research and Treatment
#24
of 71 outputs
Altmetric has tracked 25,605,018 research outputs across all sources so far. This one has received more attention than most of these and is in the 67th percentile.
So far Altmetric has tracked 4,991 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.4. 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 361,717 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 61% of its contemporaries.
We're also able to compare this research output to 71 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.