Cardiac disease classifier using Digital Twin

An cardiac disease classifier in order to diagnose cardiac diseases with artificial intelligence. 

We used both synthetic and experimental data for training our machine learning model.  Various features were extracted from synthetic and experimental hemo dynamic/acoustic factors for different cardiac diseases.

Total accuracy of the model was 93.5% for classification of 10 common cardiac diseases with only 6 features.