| Title |
A meta-analysis of the diagnostic performance of machine learning-based MRI in the prediction of axillary lymph node metastasis in breast cancer patients
|
|---|---|
| Published in |
Insights into Imaging, November 2021
|
| DOI | 10.1186/s13244-021-01034-1 |
| Pubmed ID | |
| Authors |
Chen Chen, Yuhui Qin, Haotian Chen, Dongyong Zhu, Fabao Gao, Xiaoyue Zhou |
X Demographics
The data shown below were collected from the profiles of 5 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Austria | 1 | 20% |
| United Kingdom | 1 | 20% |
| United States | 1 | 20% |
| Unknown | 2 | 40% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 3 | 60% |
| Scientists | 2 | 40% |
Mendeley readers
The data shown below were compiled from readership statistics for 28 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 28 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 4 | 14% |
| Student > Doctoral Student | 2 | 7% |
| Unspecified | 1 | 4% |
| Lecturer > Senior Lecturer | 1 | 4% |
| Librarian | 1 | 4% |
| Other | 2 | 7% |
| Unknown | 17 | 61% |
| Readers by discipline | Count | As % |
|---|---|---|
| Engineering | 4 | 14% |
| Biochemistry, Genetics and Molecular Biology | 2 | 7% |
| Medicine and Dentistry | 2 | 7% |
| Nursing and Health Professions | 1 | 4% |
| Chemical Engineering | 1 | 4% |
| Other | 2 | 7% |
| Unknown | 16 | 57% |
Attention Score in Context
This research output has an Altmetric Attention Score of 11. 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 22 January 2024.
All research outputs
#3,233,422
of 25,208,845 outputs
Outputs from Insights into Imaging
#188
of 1,190 outputs
Outputs of similar age
#69,887
of 436,334 outputs
Outputs of similar age from Insights into Imaging
#11
of 46 outputs
Altmetric has tracked 25,208,845 research outputs across all sources so far. Compared to these this one has done well and is in the 87th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,190 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.1. This one has done well, scoring higher than 84% 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 436,334 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 83% of its contemporaries.
We're also able to compare this research output to 46 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 78% of its contemporaries.