AI-powered ECG Analysis for Deadly Arrhythmias and ICI Myocarditis
Efficient Deep Learning Approaches for the Rapid and Interpretable Detection of Deadly Arrhythmias in ECG Data
Groupe Hospitalier Pitie-Salpetriere
127,000 participants
Jan 1, 2026
OBSERVATIONAL
Conditions
Summary
ELDORA is a non-interventional observational data-science study aiming to develop and validate clinical-grade artificial intelligence tools applied to electrocardiogram (ECG) data. The project will standardize heterogeneous ECGs, create the ECGInsight harmonized database, and train interpretable models for life-threatening arrhythmia risk prediction, especially Torsades-de-Pointes/long QT syndrome and immune checkpoint inhibitor (ICI)-induced myocarditis. The project uses existing and ongoing national and international ECG cohorts with de-identified clinical metadata; AI outputs are intended for research/model development and are not used to drive patient care during the study.
Eligibility
Inclusion Criteria3
- subjects included in participating existing or ongoing ECG cohorts made available to ECGInsight
- availability of ECG data (digital waveform or scanned/paper ECG suitable for digitization) and relevant clinical/demographic metadata
- data use permitted by applicable ethical, regulatory, contractual and GDPR requirements.
Exclusion Criteria1
- datasets or individual records for which required approvals, data-sharing agreements, de-identification/anonymization, or minimum ECG/metadata quality requirements are not met. No interventional study treatment is assigned.
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Locations(1)
View Full Details on ClinicalTrials.gov
For the most up-to-date information, visit the official listing.
NCT07644715