Predicting atrial fibrillation and flutter using BEHRT and identifying multimorbidity patterns using BERTopic
The combination of BEHRT and BERTopic demonstrated the ability to predict atrial fibrillation and flutter based on multimorbid histories while identifying distinct sex-specific disease patterns. These findings underscore the potential for artificial intelligence to enhance personalized healthcare and optimize prevention and management strategies for chronic conditions.
Authors
- H K Kim
- Samina Park
- Yeonjae Kim (ORCID: https://orcid.org/0000-0002-8528-9477)
- Sangeun Bae (ORCID: https://orcid.org/0000-0002-0710-5839)
- Bomi Park
Institutions
- Yonsei University (KR)
- Seoul National University Hospital (KR)
- Chung-Ang University (KR)
Publication Details
- Journal
- Frontiers in Digital Health
- Published
- 2026-02-05
- DOI
- https://doi.org/10.3389/fdgth.2026.1722338
- Primary Topic
- Atrial Fibrillation Management and Outcomes
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Research Foundation
- National Research Foundation of Korea
- Ministry of Science and ICT, South Korea