Artificial intelligence-enabled electrocardiography to predict impending episodes of ventricular tachycardia in individuals under continuous heart rhythm monitoring
This is a protocol for a Cochrane Review (prognosis). The objectives are as follows: To identify and evaluate AI-based prognostic models, in development and external validation studies, which predict impending episodes of ventricular tachycardia from continuous surface electrocardiogram (ECG) recordings in individuals at elevated risk for ventricular arrhythmias due to any relevant underlying condition.
Authors
- Maria Bampa (ORCID: https://orcid.org/0000-0003-0927-8239)
- Theo Papaioannou (ORCID: https://orcid.org/0000-0001-5228-4242)
- Panagiotis Papapetrou (ORCID: https://orcid.org/0000-0002-4632-4815)
- Panteleimon Pantelidis (ORCID: https://orcid.org/0000-0001-5394-832X)
- Ioannis Gialamas (ORCID: https://orcid.org/0009-0003-1700-8244)
- Michael Spartalis
- A Gkoliopoulou
- Ioanna Miliou
- Polychronis Dilaveris
- Evangelos Oikonomou
- Gerasimos Siasos
Institutions
- Brigham and Women's Hospital (US)
- Stockholm University (SE)
- National and Kapodistrian University of Athens (GR)
- Laiko General Hospital of Athens (GR)
- Sotiria General Hospital (GR)
Publication Details
- Journal
- Cochrane Database of Systematic Reviews
- Published
- 2026-03-02
- DOI
- https://doi.org/10.1002/14651858.cd016334
- Primary Topic
- ECG Monitoring and Analysis
- Type
- article
- Field-Weighted Citation Impact
- 0.00