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 |
Development and validation of machine learning-based risk prediction models of oral squamous cell carcinoma using salivary autoantibody biomarkers
|
|---|---|
| Published in |
BMC Oral Health, November 2022
|
| DOI | 10.1186/s12903-022-02607-2 |
| Pubmed ID | |
| Authors |
Yi-Ju Tseng, Yi-Cheng Wang, Pei-Chun Hsueh, Chih-Ching Wu |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Taiwan | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 24 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 24 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 4 | 17% |
| Student > Bachelor | 2 | 8% |
| Student > Postgraduate | 2 | 8% |
| Student > Ph. D. Student | 1 | 4% |
| Unspecified | 1 | 4% |
| Other | 2 | 8% |
| Unknown | 12 | 50% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 3 | 13% |
| Engineering | 2 | 8% |
| Computer Science | 2 | 8% |
| Agricultural and Biological Sciences | 1 | 4% |
| Unspecified | 1 | 4% |
| Other | 2 | 8% |
| Unknown | 13 | 54% |
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 12 December 2022.
All research outputs
#15,695,398
of 23,322,966 outputs
Outputs from BMC Oral Health
#768
of 1,530 outputs
Outputs of similar age
#238,731
of 444,903 outputs
Outputs of similar age from BMC Oral Health
#32
of 81 outputs
Altmetric has tracked 23,322,966 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,530 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.1. This one is in the 36th percentile – i.e., 36% 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 444,903 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 35th percentile – i.e., 35% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 81 others from the same source and published within six weeks on either side of this one. This one is in the 48th percentile – i.e., 48% of its contemporaries scored the same or lower than it.