The research project titled “Machine Learning-Guided Differentiation of RVOT and LVOT Arrhythmias”, authored by the Biomedical Engineering Laboratory of the National Technical University of Athens (Supervisor: Prof. G. Matsopoulos, Director) and the 1st University Cardiology Clinic of the National and Kapodistrian University of Athens (Supervisor: Prof. D. Tsiachris, Director: Prof. K. Tsioufis), was awarded third place among 92 submissions at the international conference of the International Society for Holter and Noninvasive Electrocardiology (ISHNE) and the International Society of Electrocardiology (ISE), held in Thessaloniki from May 30 to June 1, 2025.
The study employed machine learning techniques to differentiate the origin of ventricular ectopic beats arising from the right or left ventricular outflow tract, contributing significantly to the accuracy of pre-procedural diagnosis and the planning of therapeutic strategies.
