Mind the Gap: Papers about the Challenge
The following paper describes the PhysioNet/Computing in Cardiology Challenge. Please cite this publication when referencing the Challenge.
The following papers were presented at the Computing in Cardiology Conference.
Estimation
of Missing Data in Multi-channel Physiological Time-series by Average
Substitution with Timing from a Reference Channel
P Langley, S King, K Wang, D Zheng, R Giovannini, M Bojarnejad, A Murray
Reconstruction of Missing Physiological Signals Using Artificial Neural Networks
AM Sullivan, H Xia, JC McBride, X Zhao
Reconstruction of Missing Cardiovascular Signals using Adaptive Filtering
A Hartmann
Principal
Component Analysis Based Method for Reconstruction of Fragments of
Corrupted or Lost Signal in Multilead Data Reflecting Electrical Heart
Activity and Hemodynamics
R Petrolis, R Simoliuniene, A Krisciukaitis
An Approach to Reconstruct Lost Cardiac Signals Using Pattern Matching and Neural Networks via Related Cardiac Information
TCT Ho, X Chen
Medical Multivariate Signal Reconstruction Using Recurrent Neural Network
LEV Silva, JJ Duque, MG Guzo, I Soares, R Tinós, LO Murta Jr
Reconstructing Missing Signals in Multi-Parameter Physiologic Data by Mining the Aligned Contextual Information
Y Li, Y Sun, P Sondhi, L Sha, C Zhai
Filling in the Gap: a General Method Using Neural Networks
R Rodrigues
A Wavelet Scheme for Reconstruction of Missing Sections in Time Series Signals
TR Rocha, SP Paredes, JH Henriques
Reconstruction of Multivariate Signals Using Q-Gaussian Radial Basis Function Network
LEV Silva, JJ Duque, R Tinós, LO Murta Jr