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A web-based data visualization tool for the MIMIC-II database

Overview of attention for article published in BMC Medical Informatics and Decision Making, February 2016
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (71st percentile)
  • High Attention Score compared to outputs of the same age and source (81st percentile)

Mentioned by

twitter
5 tweeters

Citations

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12 Dimensions

Readers on

mendeley
71 Mendeley
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Title
A web-based data visualization tool for the MIMIC-II database
Published in
BMC Medical Informatics and Decision Making, February 2016
DOI 10.1186/s12911-016-0256-9
Pubmed ID
Authors

Joon Lee, Evan Ribey, James R. Wallace

Abstract

Although MIMIC-II, a public intensive care database, has been recognized as an invaluable resource for many medical researchers worldwide, becoming a proficient MIMIC-II researcher requires knowledge of SQL programming and an understanding of the MIMIC-II database schema. These are challenging requirements especially for health researchers and clinicians who may have limited computer proficiency. In order to overcome this challenge, our objective was to create an interactive, web-based MIMIC-II data visualization tool that first-time MIMIC-II users can easily use to explore the database. The tool offers two main features: Explore and Compare. The Explore feature enables the user to select a patient cohort within MIMIC-II and visualize the distributions of various administrative, demographic, and clinical variables within the selected cohort. The Compare feature enables the user to select two patient cohorts and visually compare them with respect to a variety of variables. The tool is also helpful to experienced MIMIC-II researchers who can use it to substantially accelerate the cumbersome and time-consuming steps of writing SQL queries and manually visualizing extracted data. Any interested researcher can use the MIMIC-II data visualization tool for free to quickly and conveniently conduct a preliminary investigation on MIMIC-II with a few mouse clicks. Researchers can also use the tool to learn the characteristics of the MIMIC-II patients. Since it is still impossible to conduct multivariable regression inside the tool, future work includes adding analytics capabilities. Also, the next version of the tool will aim to utilize MIMIC-III which contains more data.

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

Geographical breakdown

Country Count As %
United States 1 1%
Belgium 1 1%
Canada 1 1%
Unknown 68 96%

Demographic breakdown

Readers by professional status Count As %
Student > Master 13 18%
Researcher 12 17%
Student > Ph. D. Student 11 15%
Student > Doctoral Student 7 10%
Student > Bachelor 7 10%
Other 10 14%
Unknown 11 15%
Readers by discipline Count As %
Computer Science 21 30%
Medicine and Dentistry 15 21%
Business, Management and Accounting 3 4%
Agricultural and Biological Sciences 3 4%
Nursing and Health Professions 3 4%
Other 13 18%
Unknown 13 18%

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 08 February 2016.
All research outputs
#1,598,615
of 7,140,824 outputs
Outputs from BMC Medical Informatics and Decision Making
#304
of 898 outputs
Outputs of similar age
#89,052
of 319,388 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#6
of 32 outputs
Altmetric has tracked 7,140,824 research outputs across all sources so far. Compared to these this one has done well and is in the 77th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 898 research outputs from this source. They receive a mean Attention Score of 4.3. This one has gotten more attention than average, scoring higher than 65% 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 319,388 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 71% of its contemporaries.
We're also able to compare this research output to 32 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 81% of its contemporaries.