Efficacy and Safety of Anticoagulation Treatment in COVID-19 Patient Subgroups Identified by Clinical-Based Stratification and Unsupervised Machine Learning: A Matched Cohort Study
Pharmacology, Toxicology and Pharmaceutical Science
1
4%
Computer Science
1
4%
Other
3
11%
Unknown
15
54%
Attention Score in Context
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 10 January 2022.
All research outputs
#20,310,658
of 22,851,489 outputs
Outputs from Frontiers in Medicine
#4,901
of 5,671 outputs
Outputs of similar age
#407,440
of 497,922 outputs
Outputs of similar age from Frontiers in Medicine
#478
of 600 outputs
Altmetric has tracked 22,851,489 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 5,671 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 13.0. This one is in the 1st percentile – i.e., 1% 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 497,922 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 600 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
