AI Model to recognize cardiac arrhythmia with convolutional nueronal network

Overview

This repository contains the entire process for training (data processing and segmentation) a convolutional neural network (CNN) model designed to recognize cardiac arrhythmias using the MIT-BIH arrhythmia database.

Contents

• model.ipynb: Jupyter notebook containing the CNN model's implementation and training.
• ten_file_model.keras: Keras model file.
• mitbih_database: Folder containing data files (not detailed).

Getting Started

To use this model, clone the repository and ensure you have Jupyter Notebook and TensorFlow installed.

Requirements

• TensorFlow
• Keras
• NumPy

Usage

Open model.ipynb in Jupyter Notebook and run the cells to train the model or make predictions using the pre-trained model.

Important Note

This project was taken from a public Kaggle database and was adapted with substantial changes by: Andres F. Vargas and Bryam Villalobos

Contributing

Contributions to improve the model or extend its capabilities are welcome. Please submit a pull request or open an issue to discuss your ideas.