imdehydrated/heartDiseaseClassifier
Binary ECG classification (NORM vs Abnormal) using SVM, Random Forest, K-Means, and a 1D CNN on the PTB-XL dataset.
Python0 stars0 forks
What it does
The Heart Disease ECG Classifier uses machine learning and deep learning techniques to classify 1-D ECG signals as normal or abnormal. This project is significant for improving early detection of heart diseases using a large, publicly available dataset.
Star history
Tracking
- Last trending
- 2026-02-21
Creator kit
Hook
Explore how machine learning can revolutionize heart disease detection with this ECG classifier!
Content angles
- A tutorial on implementing the ECG classifier using the PTB-XL dataset.
- An analysis of the performance of different models (SVM, Random Forest, CNN) in ECG classification.
- A discussion on the importance of early heart disease detection and how technology can aid in this.
Who should care
Data scientists, healthcare professionals, and machine learning enthusiasts interested in health tech.