↓ Skip to main content

A clinical text classification paradigm using weak supervision and deep representation

Overview of attention for article published in BMC Medical Informatics and Decision Making, January 2019
Altmetric Badge

About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (62nd percentile)
  • Above-average Attention Score compared to outputs of the same age and source (59th percentile)

Mentioned by

twitter
5 tweeters

Citations

dimensions_citation
14 Dimensions

Readers on

mendeley
25 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
A clinical text classification paradigm using weak supervision and deep representation
Published in
BMC Medical Informatics and Decision Making, January 2019
DOI 10.1186/s12911-018-0723-6
Pubmed ID
Authors

Yanshan Wang, Sunghwan Sohn, Sijia Liu, Feichen Shen, Liwei Wang, Elizabeth J. Atkinson, Shreyasee Amin, Hongfang Liu

Twitter Demographics

The data shown below were collected from the profiles of 5 tweeters 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 25 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 25 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 5 20%
Other 4 16%
Student > Bachelor 4 16%
Researcher 3 12%
Student > Ph. D. Student 2 8%
Other 3 12%
Unknown 4 16%
Readers by discipline Count As %
Computer Science 7 28%
Medicine and Dentistry 6 24%
Engineering 5 20%
Biochemistry, Genetics and Molecular Biology 2 8%
Unknown 5 20%

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 16 November 2019.
All research outputs
#4,465,889
of 15,037,508 outputs
Outputs from BMC Medical Informatics and Decision Making
#511
of 1,365 outputs
Outputs of similar age
#139,465
of 378,854 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#34
of 83 outputs
Altmetric has tracked 15,037,508 research outputs across all sources so far. This one has received more attention than most of these and is in the 70th percentile.
So far Altmetric has tracked 1,365 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.1. This one has gotten more attention than average, scoring higher than 62% 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 378,854 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 62% of its contemporaries.
We're also able to compare this research output to 83 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 59% of its contemporaries.