To develop a computer processable algorithm, capable of running automated searches of routine data that flag miscoded and misclassified cases of diabetes for subsequent clinical review.
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 15 September 2011.
All research outputs
#20,107,308
of 24,717,821 outputs
Outputs from Diabetic Medicine
#3,284
of 3,781 outputs
Outputs of similar age
#125,829
of 160,455 outputs
Outputs of similar age from Diabetic Medicine
#39
of 50 outputs
Altmetric has tracked 24,717,821 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 3,781 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.8. This one is in the 3rd percentile – i.e., 3% 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 160,455 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 9th percentile – i.e., 9% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 50 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.
