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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Detection of pulmonary ground-glass opacity based on deep learning computer artificial intelligence
|
|---|---|
| Published in |
BioMedical Engineering OnLine, January 2019
|
| DOI | 10.1186/s12938-019-0627-4 |
| Pubmed ID | |
| Authors |
Wenjing Ye, Wen Gu, Xuejun Guo, Ping Yi, Yishuang Meng, Fengfeng Han, Lingwei Yu, Yi Chen, Guorui Zhang, Xueting Wang |
X Demographics
The data shown below were collected from the profiles of 4 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Brazil | 1 | 25% |
| Turkey | 1 | 25% |
| Netherlands | 1 | 25% |
| Unknown | 1 | 25% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 50% |
| Practitioners (doctors, other healthcare professionals) | 2 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 121 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 121 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Unspecified | 38 | 31% |
| Student > Ph. D. Student | 11 | 9% |
| Researcher | 9 | 7% |
| Student > Master | 9 | 7% |
| Student > Doctoral Student | 6 | 5% |
| Other | 18 | 15% |
| Unknown | 30 | 25% |
| Readers by discipline | Count | As % |
|---|---|---|
| Unspecified | 38 | 31% |
| Medicine and Dentistry | 12 | 10% |
| Engineering | 9 | 7% |
| Computer Science | 8 | 7% |
| Nursing and Health Professions | 4 | 3% |
| Other | 17 | 14% |
| Unknown | 33 | 27% |
Attention Score in Context
This research output has an Altmetric Attention Score of 3. 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 02 July 2019.
All research outputs
#13,058,036
of 23,124,001 outputs
Outputs from BioMedical Engineering OnLine
#318
of 826 outputs
Outputs of similar age
#201,408
of 437,601 outputs
Outputs of similar age from BioMedical Engineering OnLine
#5
of 9 outputs
Altmetric has tracked 23,124,001 research outputs across all sources so far. This one is in the 43rd percentile – i.e., 43% of other outputs scored the same or lower than it.
So far Altmetric has tracked 826 research outputs from this source. They receive a mean Attention Score of 4.7. This one has gotten more attention than average, scoring higher than 61% 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 437,601 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 53% of its contemporaries.
We're also able to compare this research output to 9 others from the same source and published within six weeks on either side of this one. This one has scored higher than 4 of them.