flaviagiammarino/ecg-classification

PyTorch implementation of FCN and LSTM-FCN models for ECG classification

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amiruzzaman1/ECG-Classification-Project

his project involves the classification of ECG (Electrocardiogram) readings to determine whether they are normal or abnormal. The dataset consists of rows, each representing a complete ECG of a patient with 140 data points (readings).

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AlirezaKhodabakhsh/ECGNet

ECGNet, leveraging PyTorch, classifies ECG signals with 96% accuracy, using a streamlined model of around 1300 parameters, trained on Kaggle's PTB Diagnostic ECG Database

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carrliitos/ecg_classification

Predicting Cardiac Wellnes: Using a Multi-Layer Perceptron on ECG Data

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ywan3223/ECG-Heartbeat-Classification

ECG Arrhythmia Detection with ResNet and Transfer Learning

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pnhuy/ecg-analysis

Machine learning-based detection of cardiovascular disease using ECG signals: performance vs. complexity

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dchung1209/ECGHearbeat

ECG(electrocardiogram) heartbeat multi-class classification

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SinaGhaffarzadeh/Classicification-of-8-Types-of-Sensitive-Cardiac-Arrhythmias-Using-Deep-Learning

An artificial intelligence implementation on 8 arrhythmias that consist of Atrial Fibrillation, Atrial Flutter, Premature Atrial Contraction, Sinus Bradycardia, Supraventricular Tachycardia, Sinus Rhythm, Sinus Tachycardia, Premature Ventricular Contraction.

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Soham042328/Artificial-Intelligence-in-Heart-Modelling

• Developed and implemented ensemble-based machine learning models for ECG signal classification, enhancing accuracy and reliability. • Addressed challenges in data preprocessing, feature engineering, and class imbalance in ECG datasets. • Demonstrated the clinical implications of accurate ECG classification for enhanced patient care and diagnosis

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ForceLightning/AAI1001_Project

Archive for an AAI1001 project on Arrhythmia classification with a Temporal Convolutional Network with Grad-CAM Explainability

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john-fante/normal_heartbeat_vs_myocardial_infarction_classification

Basic ECG time series classification with Keras (Normal heartbeat vs Myocardial Infarction)

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deadly4/arrhydet

Arrhythmia detector based on machine learning algorithms

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marcusnk237/dataset_gradcam_plus_plus

dataset level explanability for 1d signal

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Senume/Person-identification-using-ECG

This repository contains the implementation of a novel approach to identify the subjects using PQRST fragments of the electrocardiogram (ECG) signal.

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4ldk/LCCNN

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Senume/ECG_analysis_DMD

Implementation of a study which attempt to evaluate whether the stability of decomposed ECG subsystems can be analyzed in order to effectively investigate the overall performance of ECG signals, and aid in disease diagnosis

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Red1C3/ecg-heartbeat-categorization-cnn-mlp

Neural networks trained to categorize heartbeat ECG's using mitbit and ptbdb datasets

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giovannidispoto/applied-ai-in-biomedicine-ECG-classifier

1D-CNN that is able to predict, in an inter-patient fashion, if a beat is Normal, Premature Ventricular Complex or Premature Atrial Complex relying on only a portion of the ECG.

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insung3511/ecg-dbn 📦

ECG Classification of Normal and Abnormal with GB-DBN Model (pytorch)

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ZakiKurdya/automatic-ecg-diagnosis Fork of antonior92/automatic-ecg-diagnosis

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".

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IkerValdelvira/TFG_PRAFAI

Software developed to carry out the End-of-Degree Project PRAFAI (Prediction of Recurrence of Atrial Fibrillation using Artificial Intelligence).

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