
ESC TV Today – Your Cardiovascular News Season 4 - Ep1: Extended interview on Digital solutions in arrhythmias
Jan 22, 2026
Fleur Tjong, a cardiology expert at Amsterdam UMC specializing in digital cardiology and AI in electrophysiology, engages in a rich discussion about the future of heart health. She explores how AI can predict atrial fibrillation risks using ECG data and emphasizes personalized approaches to monitoring. Fleur also highlights the importance of integrating wearable data into electronic health records without overwhelming clinics. Additionally, she discusses training for clinicians in digital tools, the health economics of remote monitoring, and her vision for AI's role in arrhythmia care over the next five years.
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AI ECG Predicts AF Risk After Cryptogenic Stroke
- AI on sinus-rhythm 12‑lead ECG can identify patients at higher risk of future atrial fibrillation after embolic stroke of undetermined origin.
- Fleur Tjong cautions we should confirm AF before changing therapy but use AI to target longer monitoring.
Burden Is About Patterns, Not Single Thresholds
- Atrial fibrillation burden is the proportion of time a patient is in AF and depends on monitoring method and time window.
- Fleur Tjong emphasizes patterns and trends (rising burden, prolonged episodes, symptom correlation) over universal thresholds.
Triage Wearable Alerts Before EHR Integration
- Integrate device data into EHRs with targeted triage to avoid overwhelming clinics.
- Establish infrastructure so only relevant, triaged alerts reach outpatient workflows.
