Mind the Gap: Papers about the Challenge


The following paper describes the Computing in Cardiology Challenge. Please cite this publication when referencing the Challenge.

The following papers were presented at Computing in Cardiology.

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

PhysioNet 2010 Challenge: a Robust Multi-Channel Adaptive Filtering Approach to the Estimation of Physiological Recordings
I Silva

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

The Multi-parameter Physiologic Signal Reconstruction by means of Wavelet Singularity Detection and Signal Correlation
W Wu

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