Machine Learning-Based Clustering Using a 12-Lead Electrocardiogram in Patients With a Implantable Cardioverter Defibrillator to Identify Future Ventricular Arrhythmia
We highlight the potential of ML-based clustering using 12-lead ECGs to help in the risk stratification of ventricular arrhythmia. Future research in a larger multicenter setting may provide further insights and refine ICD indications.
Authors
- Atsuya Shimizu (ORCID: https://orcid.org/0000-0001-5909-4716)
- Tetsuo Sasano
- Mitsuhiro Nishizaki
- Eiko Sakai
- Nobutaka Katoh
- Masato Shimizu (ORCID: https://orcid.org/0000-0003-1237-7633)
- Hiroshi Shimada (ORCID: https://orcid.org/0000-0002-4049-6376)
- Makoto Suzuki (ORCID: https://orcid.org/0009-0007-4761-4877)
- Ryo Tateishi (ORCID: https://orcid.org/0000-0003-2695-1106)
Institutions
- Tokyo Medical and Dental University (JP)
- Yokohama Minami Kyosai Hospital (JP)
- Odawara Municipal Hospital (JP)
Publication Details
- Journal
- Circulation Journal
- Published
- 2024-09-30
- DOI
- https://doi.org/10.1253/circj.cj-24-0269
- Citations
- 6
- Primary Topic
- ECG Monitoring and Analysis
- Type
- article
- Field-Weighted Citation Impact
- 2.41