NDLI: Predicting acute hypotensive episodes: The 10th annual PhysioNet/Computers in Cardiology Challenge

Content Provider	IEEE Xplore Digital Library
Author	Moody, G.B. Lehman, L.H.
Copyright Year	2009
Description	Author affiliation: Massachusetts Institute of Technology, Cambridge, USA (Moody, G.B.; Lehman, L.H.)
Abstract	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 were asked to forecast the occurrence of an AHE up to an hour in advance, in two groups of ICU patient records from the MIMIC II Database, drawing on data that included at least 10 hours of physiologic waveforms, time series, and accompanying clinical data prior to the one-hour forecast window. In event 1, most participants were able to identify without errors, in a group of 10 high-risk patients receiving pressor medication, which five of the patients experienced AHEs during the forecast window. In event 2, participants were able to classify correctly as many as 37 (93%) of a diverse group of 40 patients, including nearly all of those who experienced AHEs.
Starting Page	541
Ending Page	544
File Size	95658
Page Count	4
File Format	PDF
ISBN	9781424472819
ISSN	02766547
e-ISBN	9781424472826
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-09-13
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Computers in Cardiology(CinC)
Subject Keyword	Cardiology Databases Arterial blood pressure Loss measurement Biomedical monitoring Medical treatment Education Hospitals Patient monitoring Myocardium
Content Type	Text
Resource Type	Article

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Predicting acute hypotensive episodes: the 10th annual physionet/computers in cardiology challenge.

Predicting acute hypotensive episodes: The 10th annual PhysioNet/Computers in Cardiology Challenge

Predicting Acute Hypotensive Episodes: The 10th Annual PhysioNet/Computers in Cardiology Challenge

Computers in Cardiology / Physionet Challenge 2009: Predicting acute hypotensive episodes

Computers in Cardiology / Physionet Challenge 2009: Predicting acute hypotensive episodes

Computers in Cardiology / Physionet Challenge 2009: Predicting Acute Hypotensive Episodes

Forecasting acute hypotensive episodes in intensive care patients based on a peripheral arterial blood pressure waveform. Computers in Cardiology 2009;36

Forecasting acute hypotensive episodes in intensive care patients based on a peripheral arterial blood pressure waveform

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Predicting acute hypotensive episodes: The 10th annual PhysioNet/Computers in Cardiology Challenge

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