/IEEE-ECG-Ensemble-XGBoost

👨‍💻 Developed AI Models - Ensemble of Random Forest & SVM and XGBoost classifiers to classify five types of Arrhythmic Heartbeats from ECG signals - published by IEEE.

Primary LanguageJupyter NotebookMIT LicenseMIT

ECG-Ensemble-Random-Forest-SVM

Using Ensemble of Random Forest and SVM as the classifier to develop an AI Model that can classify five different types of Arrhythmic Heartbeats from ECG Signals using the MIT-BIH Arrhythmia Dataset.

Research Paper published in IEEE Journal, Transactions on Artificial Intelligence (TAI): link to paper

ieee-ecg-paper

ECG-XGBoost

Improving and preparing an even better model than the above published one.

Using XGBoost as the classifier to develop an AI Model that can classify five different types of Arrhythmic Heartbeats from ECG Signals using the MIT-BIH Arrhythmia Dataset.