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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Detection of pulmonary embolism severity using clinical characteristics, hematological indices, and machine learning techniques
|
|---|---|
| Published in |
Frontiers in Neuroinformatics, December 2022
|
| DOI | 10.3389/fninf.2022.1029690 |
| Pubmed ID | |
| Authors |
Hang Su, Zhengyuan Han, Yujie Fu, Dong Zhao, Fanhua Yu, Ali Asghar Heidari, Yu Zhang, Yeqi Shou, Peiliang Wu, Huiling Chen, Yanfan Chen |
X Demographics
The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 2 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 16 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 16 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 3 | 19% |
| Student > Postgraduate | 2 | 13% |
| Lecturer | 2 | 13% |
| Unspecified | 1 | 6% |
| Lecturer > Senior Lecturer | 1 | 6% |
| Other | 2 | 13% |
| Unknown | 5 | 31% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 4 | 25% |
| Business, Management and Accounting | 2 | 13% |
| Computer Science | 2 | 13% |
| Pharmacology, Toxicology and Pharmaceutical Science | 1 | 6% |
| Unspecified | 1 | 6% |
| Other | 1 | 6% |
| Unknown | 5 | 31% |
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 December 2022.
All research outputs
#20,854,259
of 25,622,179 outputs
Outputs from Frontiers in Neuroinformatics
#689
of 844 outputs
Outputs of similar age
#356,570
of 482,609 outputs
Outputs of similar age from Frontiers in Neuroinformatics
#10
of 21 outputs
Altmetric has tracked 25,622,179 research outputs across all sources so far. This one is in the 10th percentile – i.e., 10% of other outputs scored the same or lower than it.
So far Altmetric has tracked 844 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.7. This one is in the 12th percentile – i.e., 12% 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 482,609 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 14th percentile – i.e., 14% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 21 others from the same source and published within six weeks on either side of this one. This one is in the 42nd percentile – i.e., 42% of its contemporaries scored the same or lower than it.