↓ Skip to main content

Mining hidden knowledge for drug safety assessment: topic modeling of LiverTox as a case study

Overview of attention for article published in BMC Bioinformatics, December 2014
Altmetric Badge

Mentioned by

twitter
1 tweeter

Citations

dimensions_citation
13 Dimensions

Readers on

mendeley
50 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
Mining hidden knowledge for drug safety assessment: topic modeling of LiverTox as a case study
Published in
BMC Bioinformatics, December 2014
DOI 10.1186/1471-2105-15-s17-s6
Pubmed ID
Authors

Ke Yu, Jie Zhang, Minjun Chen, Xiaowei Xu, Ayako Suzuki, Katarina Ilic, Weida Tong

Abstract

Given the significant impact on public health and drug development, drug safety has been a focal point and research emphasis across multiple disciplines in addition to scientific investigation, including consumer advocates, drug developers and regulators. Such a concern and effort has led numerous databases with drug safety information available in the public domain and the majority of them contain substantial textual data. Text mining offers an opportunity to leverage the hidden knowledge within these textual data for the enhanced understanding of drug safety and thus improving public health.

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 50 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Canada 1 2%
Unknown 49 98%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 9 18%
Researcher 9 18%
Student > Master 9 18%
Student > Bachelor 8 16%
Student > Doctoral Student 2 4%
Other 8 16%
Unknown 5 10%
Readers by discipline Count As %
Medicine and Dentistry 11 22%
Computer Science 11 22%
Engineering 6 12%
Agricultural and Biological Sciences 4 8%
Biochemistry, Genetics and Molecular Biology 3 6%
Other 7 14%
Unknown 8 16%

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 12 January 2015.
All research outputs
#9,906,157
of 12,373,386 outputs
Outputs from BMC Bioinformatics
#3,813
of 4,588 outputs
Outputs of similar age
#185,417
of 273,304 outputs
Outputs of similar age from BMC Bioinformatics
#136
of 168 outputs
Altmetric has tracked 12,373,386 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 4,588 research outputs from this source. They receive a mean Attention Score of 4.9. This one is in the 7th percentile – i.e., 7% 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 273,304 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 18th percentile – i.e., 18% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 168 others from the same source and published within six weeks on either side of this one. This one is in the 8th percentile – i.e., 8% of its contemporaries scored the same or lower than it.