AI Fundamentals Part 2: Explainability
Speakers
In this American College of Cardiology webinar, Dr. Ng and Dr. Kargiantoulakis go over AI explainability.
Dr Fu Siong Ng
Dr Fu Siong Ng is a consultant cardiologist based in London who specialises in arrhythmia, atrial fibrillation, cardiac (catheter) ablation, pacemakers, implantable cardioverter defibrillator (ICD) and palpitations. He practices privately at The Harley Street Clinic in Central London, BMI Syon Clinic in Brentford and Imperial Private Healthcare in West London alongside his honorary consultant cardiologist roles for Imperial College Healthcare NHS Trust and Chelsea and Westminster Hospital NHS Foundation Trust.
Dr Ng is a clinical academic and alongside his medical work, where he performs catheter ablation procedures for a range of arrhythmias such as atrial fibrillation, atrial tachycardias, atrial flutter, supraventricular tachycardia (SVT) and ventricular ectopy/tachycardia and implants cardiac devices like pacemakers, defibrillators, loop recorders and biventricular pacemakers (CRT), he conducts research into arrhythmogenic mechanisms.
Manolis Kargiantoulakis, Ph.D
Manolis Kargiantoulakis is the Senior Data Scientist for GE HealthCare Diagnostic Cardiology. He received the 2024 Edison Pioneer Award for Technological Advancement in Patient Care, through pioneering work and leadership in AI/ML algorithms for ECG interpretation.
Manolis holds a Ph.D. in experimental Particle and Nuclear Physics, with more than a decade of fundamental physics research in US National Labs. He was previously the AI/ML team leader for the Muon g-2 collaboration in Fermilab.