Machine Learning Algorithm to Predict Atrial Fibrillation Using Serial 12‐Lead ECGs Based on Left Atrial Remodeling
An ML model based on serial ECGs from an individual had greater ability to predict new-onset AF than the ML model based on a single ECG. P-wave morphologies were associated with future AF prediction.
Authors
- Jaichan Lee (ORCID: https://orcid.org/0000-0002-2730-9492)
- Sung‐Hee Song (ORCID: https://orcid.org/0000-0001-6225-2412)
- Young Keun On (ORCID: https://orcid.org/0000-0003-1025-7283)
- H. Kim
- Kyoung‐Min Park (ORCID: https://orcid.org/0000-0002-5416-9691)
- Joong-Sik Hong
- Seung‐Jung Park (ORCID: https://orcid.org/0000-0003-3288-0594)
- JaeHu Jeon
- Hye Bin Gwag (ORCID: https://orcid.org/0000-0001-5610-2872)
- Ji‐Hoon Choi (ORCID: https://orcid.org/0000-0002-5413-400X)
- Hee Sun Park (ORCID: https://orcid.org/0000-0002-9730-8524)
- Ju Youn Kim (ORCID: https://orcid.org/0009-0003-2452-4423)
- Jongwoo Kim (ORCID: https://orcid.org/0000-0002-6961-0689)
- Sung Ho Lee (ORCID: https://orcid.org/0000-0002-1018-7871)
- Soo Jin Cho (ORCID: https://orcid.org/0000-0003-4361-4988)
Institutions
- Samsung (South Korea) (KR)
- Samsung Medical Center (KR)
- Konkuk University Medical Center (KR)
- Korea Pharma (South Korea) (KR)
- Kangbuk Samsung Hospital (KR)
- Syneos Health (South Korea) (KR)
- Samsung Changwon Hospital (KR)
- Sungkyunkwan University (KR)
Publication Details
- Journal
- Journal of the American Heart Association
- Published
- 2024-09-30
- DOI
- https://doi.org/10.1161/jaha.123.034154
- Citations
- 8
- Primary Topic
- Atrial Fibrillation Management and Outcomes
- Type
- article
- Field-Weighted Citation Impact
- 3.22