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Accessing the public MIMIC-II intensive care relational database for clinical research

Overview of attention for article published in BMC Medical Informatics and Decision Making, January 2013
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (93rd percentile)
  • High Attention Score compared to outputs of the same age and source (92nd percentile)

Mentioned by

news
1 news outlet
blogs
1 blog
twitter
5 tweeters

Citations

dimensions_citation
36 Dimensions

Readers on

mendeley
67 Mendeley
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Title
Accessing the public MIMIC-II intensive care relational database for clinical research
Published in
BMC Medical Informatics and Decision Making, January 2013
DOI 10.1186/1472-6947-13-9
Pubmed ID
Authors

Daniel J Scott, Joon Lee, Ikaro Silva, Shinhyuk Park, George B Moody, Leo A Celi, Roger G Mark

Abstract

The Multiparameter Intelligent Monitoring in Intensive Care II (MIMIC-II) database is a free, public resource for intensive care research. The database was officially released in 2006, and has attracted a growing number of researchers in academia and industry. We present the two major software tools that facilitate accessing the relational database: the web-based QueryBuilder and a downloadable virtual machine (VM) image.

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

Geographical breakdown

Country Count As %
United States 3 4%
United Kingdom 1 1%
Belgium 1 1%
Canada 1 1%
Unknown 61 91%

Demographic breakdown

Readers by professional status Count As %
Student > Master 15 22%
Researcher 14 21%
Student > Ph. D. Student 12 18%
Other 5 7%
Unspecified 5 7%
Other 16 24%
Readers by discipline Count As %
Computer Science 19 28%
Medicine and Dentistry 16 24%
Engineering 15 22%
Unspecified 6 9%
Agricultural and Biological Sciences 5 7%
Other 6 9%

Attention Score in Context

This research output has an Altmetric Attention Score of 17. 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 13 December 2018.
All research outputs
#870,823
of 13,055,201 outputs
Outputs from BMC Medical Informatics and Decision Making
#65
of 1,174 outputs
Outputs of similar age
#16,924
of 254,507 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#12
of 159 outputs
Altmetric has tracked 13,055,201 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 93rd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,174 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 done particularly well, scoring higher than 94% 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 254,507 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 93% of its contemporaries.
We're also able to compare this research output to 159 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 92% of its contemporaries.