ECGML-Electrocardiography using Machine learning

14^th World Congress on Healthcare & Technologies

July 22-23, 2019 | London, UK

Wala Awad and Anas AbuZaitoun

An Najah National University, Palestine

Posters & Accepted Abstracts: J Health Med Informat

Abstract :

Electrocardiography has been used extensively in diagnoses in almost all healthcare facilities. Upgrading this tool will reform diagnosis, and is expected to improve diagnosis and patient care. Thus, this project was designed to maximize potential benefits gained when machine learning technology is incorporated into ECG analysis.
ECGML: Electrocardiography using machine learning is a project created to enhance the performance of the typical ECG scanner by widening the area of its results and improving its accuracy. Using this technology, ECG can be used to not only show basic information about the heart but also to help diagnosing more than fifteen other arrhythmias precisely. Machine learning and Googleâ??s Tensorflow were used to create a program that - when trained enough will be able to diagnose those arrhythmias in the most accurate way possible. It is an easier and a faster way to be used in this field rather than the typical way.