| 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. |
X Demographics
The data shown below were collected from the profiles of 5 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 1 | 20% |
| India | 1 | 20% |
| United States | 1 | 20% |
| Unknown | 2 | 40% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Practitioners (doctors, other healthcare professionals) | 4 | 80% |
| Science communicators (journalists, bloggers, editors) | 1 | 20% |
Mendeley readers
The data shown below were compiled from readership statistics for 94 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 3 | 3% |
| United Kingdom | 1 | 1% |
| Belgium | 1 | 1% |
| Canada | 1 | 1% |
| Unknown | 88 | 94% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 18 | 19% |
| Researcher | 16 | 17% |
| Student > Ph. D. Student | 16 | 17% |
| Other | 8 | 9% |
| Student > Doctoral Student | 6 | 6% |
| Other | 17 | 18% |
| Unknown | 13 | 14% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 24 | 26% |
| Medicine and Dentistry | 18 | 19% |
| Engineering | 18 | 19% |
| Agricultural and Biological Sciences | 5 | 5% |
| Psychology | 3 | 3% |
| Other | 11 | 12% |
| Unknown | 15 | 16% |
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
#1,809,895
of 22,691,736 outputs
Outputs from BMC Medical Informatics and Decision Making
#96
of 1,980 outputs
Outputs of similar age
#18,570
of 282,340 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#8
of 41 outputs
Altmetric has tracked 22,691,736 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 92nd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,980 research outputs from this source. They receive a mean Attention Score of 4.9. This one has done particularly well, scoring higher than 95% 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 282,340 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 41 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 80% of its contemporaries.