College of Engineering is Discussing a Master’s Thesis on (Automatic Detection of Arrhythmia)

On the grand event hall in the College of Engineering, Iraqi University, a master’s thesis was discussed by the researcher in Department of Computer Engineering (Mays Dia Hussein) entitled Automatic Detection of Arrhythmia

The message included a prediction of electrocardiogram statuses based on the use of a computer program designed to help reduce the mortality rate of people with heart disease based on one of the deep learning methods applied in this study to a convolutional neural network (CNN) to design a trained model of the ECG database, which was processed from MIT-BIT into fifteen of our categories.

The thesis aimed to improve classification performance through a proposed application of the probability density function (PDF) to fit the distribution of electrocardiogram signal over the time recorded through (CNN) design model using three classic machine learning models (SVM, RF, RNN) and evaluation by finding measurement metrics, namely accuracy, Retrieval, Simplicity, and Privacy, the model also achieved an overall accuracy of 96.67{fd4b13adeeee9a609cfac10583f373b8d433f2808785993db2034851dfbb89a5} compared to the related works.