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.
As of 1 July 2024, you may notice a temporary increase in the numbers of X profiles with Unknown location. Click here to learn more.
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output.
Click here to find out more.
X Demographics
Mendeley readers
Attention Score in Context
| Title |
Deep Learning for Automatic Image Segmentation in Stomatology and Its Clinical Application
|
|---|---|
| Published in |
Frontiers in Medical Technology, December 2021
|
| DOI | 10.3389/fmedt.2021.767836 |
| Pubmed ID | |
| Authors |
Dan Luo, Wei Zeng, Jinlong Chen, Wei Tang |
X Demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Netherlands | 1 | 33% |
| Unknown | 2 | 67% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Practitioners (doctors, other healthcare professionals) | 2 | 67% |
| Members of the public | 1 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 47 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 47 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 4 | 9% |
| Student > Bachelor | 4 | 9% |
| Student > Ph. D. Student | 3 | 6% |
| Student > Doctoral Student | 2 | 4% |
| Other | 2 | 4% |
| Other | 7 | 15% |
| Unknown | 25 | 53% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 9 | 19% |
| Engineering | 4 | 9% |
| Computer Science | 2 | 4% |
| Biochemistry, Genetics and Molecular Biology | 1 | 2% |
| Nursing and Health Professions | 1 | 2% |
| Other | 4 | 9% |
| Unknown | 26 | 55% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. 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 2024.
All research outputs
#16,068,715
of 25,859,234 outputs
Outputs from Frontiers in Medical Technology
#93
of 298 outputs
Outputs of similar age
#260,290
of 518,655 outputs
Outputs of similar age from Frontiers in Medical Technology
#9
of 19 outputs
Altmetric has tracked 25,859,234 research outputs across all sources so far. This one is in the 36th percentile – i.e., 36% of other outputs scored the same or lower than it.
So far Altmetric has tracked 298 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.1. This one has gotten more attention than average, scoring higher than 66% 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 518,655 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 48th percentile – i.e., 48% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 19 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 52% of its contemporaries.