This project will focus on predicting heart disease using neural networks. Based on attributes such as blood pressure, cholestoral levels, heart rate, and other characteristic attributes, patients will be classified according to varying degrees of coronary artery disease

Filter raw electrocardiograms(EKG), build a characteristic array based on their harmonics (decompose signal with FFT, extract amplitude/phase) and match the input heartbeat with database entries by Euclidean norm.