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ECG_MICResNet

imported

software/ecg-micresnet

12-lead ECG classification based on 1D ResNet and multi-instance classification

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

ECG_MICResNet project image
GitHub preview card for SeffyVon/ECG_MICResNet. Served by its origin, not stored here, and not covered by this registry’s licence.
record
Category
Software & Systems
Subcategory
unknown
License
BSD-3-Clause(osi)
Status
dormant
Maturity
deployed
Organization
unknown
Country
unknown
Homepage
unknown
Documentation
unknown
Tags
ecg · ecg-classification · mic · resnet
Regulatory
unknown
similar by tags

Computed from shared tags, weighted so a rare tag counts for more than a common one. These are suggestions, not curated relationships.

  • Multi-label-12-lead-ECG-abnormality-classificationecg · ecg-classification · resnet

    A Combined ResNet-DenseNet Architecture with ResU Blocks (ResU-Dense) for 12-lead ECG Abnormality Classification

  • In this project, we introduce a deep learning-based model for predicting age from 12-lead ECG data.

  • automatic-ecg-diagnosisecg · ecg-classification

    Scripts and modules for training and testing neural network for ECG automatic classification. Companion code to the paper "Automatic diagnosis of the 12-lead ECG using a deep neural network".

  • awecgecg · ecg-classification

    Flutter ECG application to Windows and Android.

  • CardioLabecg · ecg-classification

    This is the official repository for CardioLab. A machine and deep learning framework for the estimation and monitoring of laboratory abnormalities throught ECG data.

  • dot-res-lstmecg · ecg-classification

    Classification of ECG signals by dot Residual LSTM Network for anomaly detection

sources
  1. api.github.com/repos/SeffyVon/ECG_MICResNet
    retrieved 2026-08-25 · via github-api

    Machine-imported from GitHub search. Last push 2021-10-14, 7 stars, license reported as BSD-3-Clause. Category and schematic were assigned by keyword heuristics and are unreviewed.

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/v1/entries/33.json→ .entries["ecg-micresnet"]

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