Artificial Intelligence Chest X-Ray Opportunistic Screening Model for Coronary Artery Calcium Deposition: A Multi-Objective Model With Multimodal Data Fusion
Open-source fusion artificial intelligence-CXR model performed better than existing state-of-the-art models for predicting CAC scores only on internal cohort, with robust performance on external datasets. This proposed model may be useful as a robust, first-pass opportunistic screening method for cardiovascular risk from regular CXR.
Authors
- Laura M. Koepke
- Milagros Pereyra (ORCID: https://orcid.org/0000-0003-4695-8436)
- Imon Banerjee (ORCID: https://orcid.org/0000-0002-3327-8004)
- Chieh‐Ju Chao (ORCID: https://orcid.org/0000-0001-6155-0266)
- Chun‐Chin Chang (ORCID: https://orcid.org/0000-0001-6402-0754)
- Reza Arsanjani (ORCID: https://orcid.org/0000-0001-7081-4286)
- Hari Trivedi (ORCID: https://orcid.org/0000-0001-6648-8334)
- Ebram F Said
- Bhavik N. Patel (ORCID: https://orcid.org/0000-0001-5157-9903)
- Jiwoong Jeong (ORCID: https://orcid.org/0000-0001-5630-9443)
- Juan Farina (ORCID: https://orcid.org/0000-0002-5824-8485)
- Cecilia Tagle‐Cornell
- Yi‐Lin Tsai (ORCID: https://orcid.org/0000-0003-2301-0255)
- Chadi Ayoub (ORCID: https://orcid.org/0000-0001-5877-7478)
- Steven J. Lester
- Michael C. Roarke
- Chen Jung-Hsuan
Institutions
- Emory University (US)
- Taipei Veterans General Hospital (TW)
- Mayo Clinic in Arizona (US)
- Arizona State University (US)
Publication Details
- Journal
- Mayo Clinic Proceedings Digital Health
- Published
- 2025-10-28
- DOI
- https://doi.org/10.1016/j.mcpdig.2025.100300
- Citations
- 1
- Primary Topic
- Cardiac Imaging and Diagnostics
- Type
- article
- Field-Weighted Citation Impact
- 1.36