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

A deep learning-based system for automatic detection of sleep apnea from ECG signals using a hybrid 1D CNN-BiLSTM architecture with an attention mechanism. Achieves high accuracy with minimal preprocessing, making it suitable for real-time, portable diagnostic applications.

Oloche's AI Cardiologist is a deep learning web app for real-time automated classification of cardiac arrhythmias from raw ECG signals. Uses a custom 1D CNN trained on MIT-BIH database to classify heartbeats into five categories with confidence scores and visualizations for diagnostic support.

Classificação de séries temporais de sinais ECG com redes neurais convolucionais (CNN).

Patient Specific ECG Classification with 1D Convolution Neural Networks

In this project, we will perform 12-lead ECG Multi-label Classification. Specifically, we will design a multi-model utilizing the characteristics of diagnoses from the Shaoxing and Ningbo databases.

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".

Clasificación de señales de Electrocardiogramas (ECG) mediante Deep Learning. Implementación basada y entrenada con el dataset MIT-BIH. Incluye una aplicación web interactiva con Flask.

GUI версия проекта по получение ВЭКГ на основе ЭКГ и СППР на основе векторных петель

This project classifies ECG Signal as AF(Atrial Fibrillation) or Non-AF(All other rhythms).This project consist of 2 different models. A custom cnn and a transfer learning model. These model are doing the same thing with different approaches.

Convolutional neural network (CNN) classifying five arrhythmia classes using semi-supervised learning

Code repository of the paper: Beyond Supervision: Evaluating Contrastive Self-Supervised Learning Techniques for Electrocardiogram-Based Mental Stress Detection

Arrhythmia detector based on machine learning algorithms

Demo of a smartwatch based systematic health monitoring solution designed for patients with chronic conditions

ML-based solution for ECG signal processing and diagnosis classification

to practice about analysis ECG data with Machine Learning

MIT-BIH ECG classification using 1D CNN with TensorFlow3

Repository for "Inter and Intra Signal Variance in Feature Extraction and Classification of Affective State" AICS 2022