Open-access MIMIC-II database for intensive care research
Name
MIMIC2_IEEE_EMBC_2011_rev1[2].pdf
Size
169.16 KB
Format
Adobe PDF
Checksum (MD5)
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Author(s)
Lee, Joon
Scott, Daniel J.
Villarroel, Mauricio
Clifford, Gari D.
Saeed, Mohammed
Mark, Roger Greenwood
Date Issued
August 2011
Journal
Proceedings of the 33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2011
Publisher
Institute of Electrical and Electronics Engineers
Citation
Joon Lee et al. “Open-access MIMIC-II Database for Intensive Care Research.” in Proceedings of the 33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2011, IEEE, 2011. 8315–8318. Web.
Version
Author's final manuscript
Abstract
The critical state of intensive care unit (ICU) patients demands close monitoring, and as a result a large volume of multi-parameter data is collected continuously. This represents a unique opportunity for researchers interested in clinical data mining. We sought to foster a more transparent and efficient intensive care research community by building a publicly available ICU database, namely Multiparameter Intelligent Monitoring in Intensive Care II (MIMIC-II). The data harnessed in MIMIC-II were collected from the ICUs of Beth Israel Deaconess Medical Center from 2001 to 2008 and represent 26,870 adult hospital admissions (version 2.6). MIMIC-II consists of two major components: clinical data and physiological waveforms. The clinical data, which include patient demographics, intravenous medication drip rates, and laboratory test results, were organized into a relational database. The physiological waveforms, including 125 Hz signals recorded at bedside and corresponding vital signs, were stored in an open-source format. MIMIC-II data were also deidentified in order to remove protected health information. Any interested researcher can gain access to MIMIC-II free of charge after signing a data use agreement and completing human subjects training. MIMIC-II can support a wide variety of research studies, ranging from the development of clinical decision support algorithms to retrospective clinical studies. We anticipate that MIMIC-II will be an invaluable resource for intensive care research by stimulating fair comparisons among different studies.
MIT Department
Harvard University--MIT Division of Health Sciences and Technology
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike 3.0
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1109/IEMBS.2011.6092050
