Feasibility of ECG Reconstruction from Minimal Lead Sets Using Convolutional Neural Networks

Maksymilian Matyschik, Henry Mauranen, Joël Karel, Pietro Bonizzi

Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceeding › Academic › peer-review

Original language	English
Title of host publication	2020 Computing in Cardiology Conference
Number of pages	4
Volume	47
DOIs	https://doi.org/10.22489/CinC.2020.164
Publication status	Published - Sep 2020

Access to Document

@inproceedings{31bdc6ed010846c6be43e7bd44378963,

title = "Feasibility of ECG Reconstruction from Minimal Lead Sets Using Convolutional Neural Networks",

author = "Maksymilian Matyschik and Henry Mauranen and Jo{\"e}l Karel and Pietro Bonizzi",

year = "2020",

month = sep,

doi = "10.22489/CinC.2020.164",

language = "English",

volume = "47",

booktitle = "2020 Computing in Cardiology Conference",

}

TY - GEN

T1 - Feasibility of ECG Reconstruction from Minimal Lead Sets Using Convolutional Neural Networks

AU - Matyschik, Maksymilian

AU - Mauranen, Henry

AU - Karel, Joël

AU - Bonizzi, Pietro

PY - 2020/9

Y1 - 2020/9

U2 - 10.22489/CinC.2020.164

DO - 10.22489/CinC.2020.164

M3 - Conference article in proceeding

VL - 47

BT - 2020 Computing in Cardiology Conference

ER -