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cinc-challenge2017

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software/cinc-challenge2017

ECG classification from short single lead segments (Computing in Cardiology Challenge 2017 entry)

Machine-generated from the listed sources and not yet reviewed by a human.

record
Category
Software & Systems
Subcategory
unknown
License
GPL-3.0(osi)
Status
dormant
Maturity
deployed
Organization
unknown
Country
unknown
Homepage
unknown
Documentation
unknown
Tags
arrhythmia · cardiology · challenge · classification · convolutional-neural-networks · deep-convolutional-networks · ecg · physionet
Regulatory
unknown
built by · 1

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similar by tags

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    Single Lead ECG signal Acquisition and Arrhythmia Classification using Deep Learning

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    Official implementation of our IEEE:SMC 2021 paper "IMLE-Net: An Interpretable Multi-level Multi-channel Model for ECG Classification"

  • AF Classification from a short single lead ECG recording: the PhysioNet/Computing in Cardiology Challenge 2017

  • fecgsynecg · physionet

    FECGSYN toolbox for ECG and fetal ECG simulation

sources
  1. api.github.com/repos/fernandoandreotti/cinc-challenge2017
    retrieved 2026-08-05 · via github-api

    Machine-imported from GitHub search. Last push 2019-11-07, 159 stars, license reported as GPL-3.0. Category and schematic were assigned by keyword heuristics and are unreviewed.

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machine-readable

/v1/entries/48.json→ .entries["cinc-challenge2017"]

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