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

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