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X Demographics
Mendeley readers
Attention Score in Context
| Title |
3D DenseNet Deep Learning Based Preoperative Computed Tomography for Detecting Myasthenia Gravis in Patients With Thymoma
|
|---|---|
| Published in |
Frontiers in oncology, May 2021
|
| DOI | 10.3389/fonc.2021.631964 |
| Pubmed ID | |
| Authors |
Zhenguo Liu, Ying Zhu, Yujie Yuan, Lei Yang, Kefeng Wang, Minghui Wang, Xiaoyu Yang, Xi Wu, Xi Tian, Rongguo Zhang, Bingqi Shen, Honghe Luo, Huiyu Feng, Shiting Feng, Zunfu Ke |
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% |
| Mexico | 1 | 33% |
| Switzerland | 1 | 33% |
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 19 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 19 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Postgraduate | 3 | 16% |
| Researcher | 3 | 16% |
| Other | 2 | 11% |
| Student > Master | 2 | 11% |
| Student > Ph. D. Student | 1 | 5% |
| Other | 2 | 11% |
| Unknown | 6 | 32% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 4 | 21% |
| Engineering | 2 | 11% |
| Computer Science | 2 | 11% |
| Biochemistry, Genetics and Molecular Biology | 1 | 5% |
| Nursing and Health Professions | 1 | 5% |
| Other | 3 | 16% |
| Unknown | 6 | 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 29 May 2021.
All research outputs
#17,297,846
of 25,387,668 outputs
Outputs from Frontiers in oncology
#8,039
of 22,433 outputs
Outputs of similar age
#281,023
of 453,841 outputs
Outputs of similar age from Frontiers in oncology
#457
of 1,257 outputs
Altmetric has tracked 25,387,668 research outputs across all sources so far. This one is in the 21st percentile – i.e., 21% of other outputs scored the same or lower than it.
So far Altmetric has tracked 22,433 research outputs from this source. They receive a mean Attention Score of 3.0. This one has gotten more attention than average, scoring higher than 58% 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 453,841 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 1,257 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 56% of its contemporaries.