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Digital-Twin-for-Intelligent-Context-Aware-IoT-Healthcare-Systems

This project is the implementation of the experiment proposed in "Digital Twin for Intelligent Context-Aware IoT Healthcare Systems". 5 models were built and trained using real-time ECG rhythms through various machine learning algorithms to test performance on the dataset and obtain the best accuracy. The applied algorithms were Convolutional Neural Network (CNN), Multi-layer Per-ceptron (MLP), Logistic Regression (LR), Long-Short-TermMemory Network (LSTM), and Support Vector Classification(SVC)

Dataset: https://www.kaggle.com/shayanfazeli/heartbeat

Paper: https://ieeexplore.ieee.org/abstract/document/9320532

Authors:

Haya Elayan, xAnalytics Inc., Ottawa, ON, Canada. E-mails: [email protected]

Moayad Aloqaily, Mohamed Bin Zayed University of Artificial Intelligence (MBZUAI), UAE. E-mail: [email protected]

Mohsen Guizani, Mohamed Bin Zayed University of Artificial Intelligence (MBZUAI), UAE. E-mail: [email protected]

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