The eICU Collaborative Research Database (eICU-CRD), a multi-center intensive care unit (ICU) database with high granularity data for over 200,000 admissions to ICUs monitored by eICU Programs across the United States.
The current version of the eICU Collaborative Research Database v2.0 (17 May 2018).
Please see https://eicu-crd.mit.edu/ for online documentation and details on accessing the data.
When referencing this material, please cite:
@Article{PollardSD2018, author={Tom J. Pollard and Alistair E. W. Johnson and Jesse D. Raffa and Leo A. Celi and Roger G. Mark and Omar Badawi}, title={The {eICU Collaborative Research Database,} a freely available multi-center database for critical care research}, journal={Scientific Data}, year={2018}, month=sep, day={11}, volume={5}, pages={180178}, url={https://www.nature.com/articles/sdata2018178}, doi={10.1038/sdata.2018.178}, pmid={30204154}, }
Please also include the standard citation for PhysioNet:
@article{PhysioNet, author = {Goldberger, Ary L. and Amaral, Luis A. N. and Glass, Leon and Hausdorff, Jeffrey M. and Ivanov, Plamen Ch. and Mark, Roger G. and Mietus, Joseph E. and Moody, George B. and Peng, Chung-Kang and Stanley, H. Eugene}, title = {{PhysioBank}, {PhysioToolkit}, and {PhysioNet}: Components of a New Research Resource for Complex Physiologic Signals}, journal = {Circulation}, publisher = {American Heart Association, Inc.}, volume = {101}, number = {23}, year = {2000}, month = {June}, pages = {e215--e220}, doi = {10.1161/01.CIR.101.23.e215}, issn = {0009-7322}, url = {http://circ.ahajournals.org/content/101/23/e215} }
The eICU Collaborative Research Database is a large, multi-center intensive care unit (ICU) database with high granularity data for over 200,000 admissions to ICUs monitored by eICU Programs across the United States. The data is de-identified, and includes vital sign measurements, care plan documentation, severity of illness measures, diagnosis information, treatment information, and more. The freely available nature of the data will support a number of research applications into machine learning algorithms, decision support tools, and clinical knowledge generation.
The MIT/Philips eICU Clinical Database, although de-identified, still contains detailed information regarding the clinical care of patients, and must be treated with appropriate care and respect. Researchers seeking to use the full database must formally request access (PhysioNetWorks login required. If you don't have a PhysioNetWorks account, please create an account first.)
If you would like help understanding, using, or downloading content, please see our Frequently Asked Questions. If you have any comments, feedback, or particular questions regarding this page, please send them to the webmaster. Comments and issues can also be raised on PhysioNet's GitHub page. Updated Friday, 05-Oct-2018 23:28:53 CEST |
PhysioNet is supported by the National Institute of General Medical Sciences (NIGMS) and the National Institute of Biomedical Imaging and Bioengineering (NIBIB) under NIH grant number 2R01GM104987-09.
|