Liquid biopsy based on whole blood transcriptome and artificial intelligence for the prediction of coronary artery calcification: a pilot study
In this pilot study, an AI model integrating whole blood transcriptome data with clinical risk factors demonstrated the ability to predict CAC, providing incremental value over clinical models. Further studies are needed to achieve more robust validation.
Authors
- Alejandra Rubilar (ORCID: https://orcid.org/0000-0002-7417-5423)
- Nelba Pérez (ORCID: https://orcid.org/0000-0002-8193-4168)
- Alejandro La Greca (ORCID: https://orcid.org/0000-0002-0309-7683)
- Soledad Rodríguez-Varela
- Estefanía Mancini (ORCID: https://orcid.org/0000-0002-7308-1273)
- Alan Miqueas Möbbs
- Santiago Miriuka (ORCID: https://orcid.org/0000-0003-2402-3920)
- Rosana Poggio (ORCID: https://orcid.org/0000-0002-3339-2421)
- Ignacio Berdiñas
- Carlos Luzzani (ORCID: https://orcid.org/0000-0003-0244-1312)
- Gastón A. Rodríguez-Granillo (ORCID: https://orcid.org/0000-0003-0820-2611)
- Florencia De Lillo
- Razan Hijazi
- Claudia Solari (ORCID: https://orcid.org/0000-0002-3468-4282)
- Sarah Y Garron-Arias
- María Olivera-Mores
Institutions
- Instituto de Neurología Cognitiva (AR)
- Cambridge Consultants (United Kingdom) (GB)
- Instituto Cardiovascular de Buenos Aires (AR)
Publication Details
- Journal
- European Heart Journal - Digital Health
- Published
- 2025-05-02
- DOI
- https://doi.org/10.1093/ehjdh/ztaf042
- Primary Topic
- Coronary Interventions and Diagnostics
- Type
- article
- Field-Weighted Citation Impact
- 0.00