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X Demographics
Mendeley readers
Attention Score in Context
| Title |
The efficacy of deep learning models in the diagnosis of endometrial cancer using MRI: a comparison with radiologists
|
|---|---|
| Published in |
BMC Medical Imaging, April 2022
|
| DOI | 10.1186/s12880-022-00808-3 |
| Pubmed ID | |
| Authors |
Aiko Urushibara, Tsukasa Saida, Kensaku Mori, Toshitaka Ishiguro, Kei Inoue, Tomohiko Masumoto, Toyomi Satoh, Takahito Nakajima |
X Demographics
The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Netherlands | 1 | 33% |
| Unknown | 2 | 67% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 67% |
| Practitioners (doctors, other healthcare professionals) | 1 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 26 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 26 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Bachelor | 4 | 15% |
| Professor > Associate Professor | 3 | 12% |
| Student > Ph. D. Student | 2 | 8% |
| Other | 1 | 4% |
| Unspecified | 1 | 4% |
| Other | 1 | 4% |
| Unknown | 14 | 54% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 4 | 15% |
| Agricultural and Biological Sciences | 2 | 8% |
| Nursing and Health Professions | 2 | 8% |
| Unspecified | 1 | 4% |
| Biochemistry, Genetics and Molecular Biology | 1 | 4% |
| Other | 1 | 4% |
| Unknown | 15 | 58% |
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 07 May 2022.
All research outputs
#18,465,899
of 23,709,010 outputs
Outputs from BMC Medical Imaging
#348
of 624 outputs
Outputs of similar age
#299,445
of 443,790 outputs
Outputs of similar age from BMC Medical Imaging
#18
of 32 outputs
Altmetric has tracked 23,709,010 research outputs across all sources so far. This one is in the 19th percentile – i.e., 19% of other outputs scored the same or lower than it.
So far Altmetric has tracked 624 research outputs from this source. They receive a mean Attention Score of 2.1. This one is in the 38th percentile – i.e., 38% of its peers scored the same or lower than it.
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 443,790 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 28th percentile – i.e., 28% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 32 others from the same source and published within six weeks on either side of this one. This one is in the 46th percentile – i.e., 46% of its contemporaries scored the same or lower than it.