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ecg-data

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This research addresses the critical domain of anomaly detection in real-time ECG signals, a pivotal aspect in healthcare monitoring. The study encompasses comprehensive data preprocessing, detailed analysis of ECG graphs, and the application of diverse machine learning models, including logistic regression, random forest, XGboost,LSTM.

  • Updated Oct 13, 2024
  • Jupyter Notebook

Official and maintained implementation of the paper "Exploring Novel Algorithms for Atrial Fibrillation Detection by Driving Graduate Level Education in Medical Machine Learning" (ECG-DualNet) [Physiological Measurement 2022, EMBC 2023].

  • Updated Jul 18, 2023
  • Python

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