This repository contains the code and resources for the research project titled "Arrhythmia Detection using Neural Networks Transformer Architecture." The project aims to develop an effective model for accurately classifying arrhythmias based on ECG data using a Transformer-based architecture.
- Introduction
- Requirements
- Installation
Arrhythmia detection is an important task in cardiology that involves identifying irregularities in heart rhythms using ECG recordings. This project explores the use of a Transformer-based architecture combined with a dense network for accurate arrhythmia classification. The model leverages the temporal dependencies and patterns within ECG sequences to capture key features associated with different arrhythmias.
- Python 3.x
- TensorFlow
- NumPy
- Pandas
- Matplotlib For detailed package requirements, please refer to the requirements.txt file.
Clone this repository to your local machine. Install the required packages by running pip install -r requirements.txt. Ensure that you have the necessary ECG dataset available for training and testing.