Predicting Acute Hypotensive Episodes: Papers about the Challenge
The following paper describes the PhysioNet/Computing in Cardiology Challenge. Please cite this publication when referencing the Challenge.
Predicting Acute Hypotensive Episodes: The 10th
Annual PhysioNet/Computers in Cardiology Challenge
GB Moody, LH Lehman
The following papers were presented at the Computing in Cardiology Conference.
Forecasting Acute Hypotensive Episodes in Intensive Care Patients
Based on a Peripheral Arterial Blood Pressure Waveform
X Chen, D Xu, G Zhang, R Mukkamala
Prediction of Acute Hypotensive Episodes Using Neural Network Multi-models
JH Henriques, TR Rocha
Predicting Acute Hypotensive Episodes from Mean
Arterial Pressure
P Langley, S King, D Zheng, EJ Bowers, K Wang, J Allen, A Murray
A Rule-Based Approach for the Prediction of
Acute Hypotensive Episodes
MA Mneimneh, RJ Povinelli
Predicting the Occurrence of Acute Hypotensive
Episodes: The PhysioNet Challenge
F Chiarugi, I Karatzanis, V Sakkalis, I Tsamardinos, Th Dermitzaki,
M Foukarakis, G Vrouchos
Acute Hypotension Episode Prediction Using
Information Divergence for Feature Selection, and Non-Parametric
Methods for Classification
PA Fournier, JF Roy
A Biosignal Analysis System Applied for Developing
an Algorithm Predicting Critical Situations of High Risk Cardiac Patients
by Hemodynamic Monitoring
D Hayn, B Jammerbund, A Kollmann, G Schreier
Smoothing and Discriminating MAP Data
K Jin, NL Stockbridge
Computers in Cardiology / Physionet Challenge 2009:
Predicting Acute Hypotensive Episodes
F Jousset, M Lemay, JM Vesin
Utilizing Histogram to Identify Patients Using
Pressors for Acute Hypotension
TCT Ho, X Chen