ECG-Atrial-Fibrillation-Classification-Using-CNN
importedsoftware/ecg-atrial-fibrillation-classification-using-cnn
This is a CNN based model which aims to automatically classify the ECG signals of a normal patient vs. a patient with AF and has been trained to achieve up to 93.33% validation accuracy.
Machine-generated from the listed sources and not yet reviewed by a human.
- Category
- Software & Systems
- Subcategory
- unknown
- License
- MIT(osi)
- Status
- dormant
- Maturity
- deployed
- Organization
- unknown
- Country
- unknown
- Homepage
- animikh.me/
- Documentation
- unknown
- Tags
- 1d-cnn · 1d-convolution · atrial-fibrillation · classification · cnn-classification · cnn-keras · deep-learning · ecg
- Regulatory
- unknown
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- PhysioNet-CinC-Challenge2020-TeamUIO1d-convolution · ecg
Public repository associated with: Convolutional Neural Network and Rule-Based Algorithms for Classifying 12-lead ECGs
- Atrial_fibrillation_detection_EMDatrial-fibrillation · classification · ecg
This repository contains code reproducing an existing method to detect atrial fibrillation using empirical mode decomposition of signals. This was a lecture that I gave for graduate-level BioSignal…
- CapsNetsLASegcnn-keras
Capsule Networks and Convolutional Neural Networks for the Automated Segmentation of Left Atrium in Cardiac MRI
- Dhadkancnn-classification
An ECG Monitoring System with Real-time Analysis for Tele-medecine facilites
- DUCK-Netcnn-keras
Using DUCK-Net for polyp image segmentation. ( Nature Scientific Reports 2023 )
- automatic-ecg-diagnosisatrial-fibrillation · ecg
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".
- api.github.com/repos/animikhaich/ECG-Atrial-Fibrillation-Classification-Using-CNNretrieved 2026-08-05 · via github-api
Machine-imported from GitHub search. Last push 2021-03-21, 52 stars, license reported as MIT. Category and schematic were assigned by keyword heuristics and are unreviewed.
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