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Using the distance between sets of hierarchical taxonomic clinical concepts to measure patient similarity

Overview of attention for article published in BMC Medical Informatics and Decision Making, April 2019
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Mentioned by

twitter
1 tweeter

Readers on

mendeley
7 Mendeley
Title
Using the distance between sets of hierarchical taxonomic clinical concepts to measure patient similarity
Published in
BMC Medical Informatics and Decision Making, April 2019
DOI 10.1186/s12911-019-0807-y
Authors

Zheng Jia, Xudong Lu, Huilong Duan, Haomin Li

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 7 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 7 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 3 43%
Professor 2 29%
Lecturer 1 14%
Unspecified 1 14%
Readers by discipline Count As %
Computer Science 3 43%
Unspecified 2 29%
Medicine and Dentistry 2 29%

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 27 April 2019.
All research outputs
#11,789,325
of 13,285,014 outputs
Outputs from BMC Medical Informatics and Decision Making
#1,152
of 1,201 outputs
Outputs of similar age
#211,100
of 251,848 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#6
of 14 outputs
Altmetric has tracked 13,285,014 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 1,201 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.1. 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 251,848 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 14 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.