Title |
Identification of High-Risk Patients for Postoperative Myocardial Injury After CME Using Machine Learning: A 10-Year Multicenter Retrospective Study
|
---|---|
Published in |
International Journal of General Medicine, April 2023
|
DOI | 10.2147/ijgm.s409363 |
Pubmed ID | |
Authors |
Yuan Liu, Chen Song, Zhiqiang Tian, Wei Shen |
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 % |
---|---|---|
Nigeria | 1 | 25% |
Spain | 1 | 25% |
Unknown | 2 | 50% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 4 | 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 % |
---|---|---|
Unspecified | 9 | 38% |
Student > Master | 2 | 8% |
Lecturer > Senior Lecturer | 1 | 4% |
Student > Postgraduate | 1 | 4% |
Unknown | 11 | 46% |
Readers by discipline | Count | As % |
---|---|---|
Unspecified | 9 | 38% |
Medicine and Dentistry | 2 | 8% |
Agricultural and Biological Sciences | 1 | 4% |
Computer Science | 1 | 4% |
Unknown | 11 | 46% |
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 14 April 2023.
All research outputs
#16,281,898
of 25,711,518 outputs
Outputs from International Journal of General Medicine
#607
of 1,665 outputs
Outputs of similar age
#216,557
of 424,122 outputs
Outputs of similar age from International Journal of General Medicine
#9
of 43 outputs
Altmetric has tracked 25,711,518 research outputs across all sources so far. This one is in the 34th percentile – i.e., 34% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,665 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 11.3. This one has gotten more attention than average, scoring higher than 59% 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 424,122 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 45th percentile – i.e., 45% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 43 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 79% of its contemporaries.