Doctor Panteleimon Pantelidis

Doctor Panteleimon Pantelidis

National & Kapodistrian University of Athens, Athens (Greece)

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Panteleimon Pantelidis is a senior cardiology trainee at “Sotiria” Hospital in Athens, and a PhD researcher at the NKUA, Greece, specializing in artificial neural networks for predicting arrhythmias. He holds an MSc in Data Science from the University of Stockholm and a medical degree from AUTh, Greece. He has authored over 40 scientific publications, including 26 peer-reviewed journal papers and a book chapter. His presentations span major congresses like ESC & EHRA. Certified in various advanced medical- and biomedical data analysis-related courses, he is also proficient in English, German and conversational Swedish. An ESC Professional Member, elected Nucleus Member of the ESC e-Cardiology WG (2024-26), and an EHRA Silver Member. Reviewer for several journals, with leadership roles in organizations like SSHMS. Awarded as an EHRA e-cardiology runner-up, a YIA finalist, and also received ESC educational grants, HSC scholarships and a WHBA award. Enjoys sailing and playing guitar.

Presentations

Generative adversarial networks (GANs) to produce synthetic 12-lead electrocardiogram signals for specific and rare diseases: a novel, powerful tool towards clinical advancements

Event: ESC Congress 2024

Topic: Electrocardiogram (ECG) and Arrhythmia Analysis

Session: Young Investigator Award Session in Arrhythmias, Pacing and Electrophysiology

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Inside the "brain" of an artificial neural network: an interpretable deep learning approach to paroxysmal atrial fibrillation diagnosis from electrocardiogram signals during sinus rhythm

Event: ESC Congress 2022

Topic: Artificial Intelligence (Machine Learning, Deep Learning)

Session: e-Cardiology/Digital health - Artificial intelligence 1

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Optimising and validating deep learning approaches for diagnosing atrial fibrillation from few-lead ambulatory electrocardiogram signals

Event: EHRA 2022

Topic: Artificial Intelligence (Machine Learning, Deep Learning)

Session: e-Cardiology award session

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Doctor Panteleimon Pantelidis

Biography

Contributor content

Generative adversarial networks (GANs) to produce synthetic 12-lead electrocardiogram signals for specific and rare diseases: a novel, powerful tool towards clinical advancements

Inside the "brain" of an artificial neural network: an interpretable deep learning approach to paroxysmal atrial fibrillation diagnosis from electrocardiogram signals during sinus rhythm

Optimising and validating deep learning approaches for diagnosing atrial fibrillation from few-lead ambulatory electrocardiogram signals

ESC 365 is supported by