Individualized prediction of atrial fibrillation onset risk based on lifelogs
Apple Watch-derived lifelogs enabled individualized AF onset risk assessment and the development of a machine-learning model for optimizing ECG timing for early AF detection.
Authors
- Masaki Ieda (ORCID: https://orcid.org/0000-0003-4724-3299)
- Yoshinori Katsumata (ORCID: https://orcid.org/0000-0001-5576-5789)
- Kenji Hashimoto (ORCID: https://orcid.org/0000-0002-8892-0439)
- Hiroshi Miyama (ORCID: https://orcid.org/0000-0001-8496-8016)
- Seiji Takatsuki (ORCID: https://orcid.org/0000-0002-0251-5193)
- Keiichi Fukuda (ORCID: https://orcid.org/0000-0003-1413-0482)
- Terumasa Yamashita (ORCID: https://orcid.org/0000-0001-7090-5559)
- Masahiro Jinzaki (ORCID: https://orcid.org/0000-0002-8241-6565)
- Takehiro Kimura (ORCID: https://orcid.org/0000-0003-3532-856X)
Institutions
- Keio University Hospital (JP)
Publication Details
- Journal
- American Journal of Preventive Cardiology
- Published
- 2025-02-23
- DOI
- https://doi.org/10.1016/j.ajpc.2025.100951
- Primary Topic
- Atrial Fibrillation Management and Outcomes
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Biosense Webster