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Arrhythmia classification using ML/DL techniques

In this project, we assess various ML/DL Approaches for Cardiac Arrhythmia classification on the MIT-BIH dataset. Our objective is to offer an effective and time-saving ECG analysis solution by combining signal processing techniques with efficient deep learning models.

Dataset

MIT-BIH is a publicly available dataset. It can be found here link

Report

This project was done as part of CSCI 5890 : Machine Learning for Healthcare curriculum. Find the complete project report here link