Predicting acute hypotensive episodes: The 10th annual PhysioNet/Computers in Cardiology Challenge
This year's PhysioNet/Computers in Cardiology Challenge aimed to stimulate development of methods for identifying intensive care unit (ICU) patients at imminent risk of acute hypotensive episodes (AHEs), motivated by the possibility of improving care and survival of these patients. Participants...
Main Authors: | Moody, George B., Lehman, Li-Wei H. |
---|---|
Other Authors: | Harvard University--MIT Division of Health Sciences and Technology |
Format: | Article |
Language: | en_US |
Published: |
Institute of Electrical and Electronics Engineers
2010
|
Online Access: | http://hdl.handle.net/1721.1/60011 |
Similar Items
-
Predicting In-Hospital Mortality of ICU Patients: The PhysioNet/Computing in Cardiology Challenge 2012
by: Silva, Ikaro, et al.
Published: (2015) -
An Open-source Toolbox for Analysing and Processing PhysioNet Databases in MATLAB and Octave
by: Ikaro Silva, et al.
Published: (2014-09-01) -
Practical Lessons on 12-Lead ECG Classification: Meta-Analysis of Methods From PhysioNet/Computing in Cardiology Challenge 2020
by: Shenda Hong, et al.
Published: (2022-01-01) -
PhysioNet: Physiologic signals, time series and related open source software for basic, clinical, and applied research
by: Moody, George B., et al.
Published: (2013) -
Heart murmur detection from phonocardiogram recordings: The George B. Moody PhysioNet Challenge 2022.
by: Matthew A Reyna, et al.
Published: (2023-09-01)