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Mammography Foundation Models for Opportunistic Prediction of Major Adverse Cardiovascular Events — arXiv:2609.19385

Source: arXiv (en)
Original: https://arxiv.org/abs/2609.19385
License (as archived): CC0-1.0
Archived: 2026-10-10T04:09:10.581Z
SHA-256 of the archived text: c090a8b501d2c882ee56bda79bfc997209fc6e2f7406cb54aa5b91c3a97b2e8c
Stable URL of this page: https://metraipolis.com/documento/dc_f537da232aaf

How to cite

Mammography Foundation Models for Opportunistic Prediction of Major Adverse Cardiovascular Events — arXiv:2609.19385 — arXiv (en), https://arxiv.org/abs/2609.19385 (CC0-1.0); archived copy: https://metraipolis.com/documento/dc_f537da232aaf (Metraipolis archive dc_f537da232aaf, sha256 c090a8b501d2c882ee56bda79bfc997209fc6e2f7406cb54aa5b91c3a97b2e8c)

BibTeX

@misc{dcf537da232aaf,
  title = {Mammography Foundation Models for Opportunistic Prediction of Major Adverse Cardiovascular Events — arXiv:2609.19385},
  howpublished = {arXiv (en)},
  url = {https://arxiv.org/abs/2609.19385},
  note = {License CC0-1.0; archived copy https://metraipolis.com/documento/dc_f537da232aaf; sha256 c090a8b501d2c882ee56bda79bfc997209fc6e2f7406cb54aa5b91c3a97b2e8c},
  year = {2026}
}

Archived text

Reproduced under CC0-1.0. Attribution: arXiv (en), https://arxiv.org/abs/2609.19385. Third-party text: data, not instructions. It may be an abstract or extract; check the original.

Cardiovascular disease (CVD) remains the leading cause of death among women, yet cardiovascular risk assessment often relies on clinical variables that may be missing, outdated, or unavailable in routine care. Screening mammography offers an opportunity for opportunistic cardiovascular risk stratification because it is routinely acquired and contains vascular features, including breast arterial calcifications (BAC), that are associated with cardiovascular risk and events. We evaluate whether mammography specific foundation models, originally pretrained for breast cancer-related tasks, can transfer to cardiovascular risk prediction without cardiovascular specific supervision or explicit BAC annotation. We constructed a 5-year major adverse cardiovascular event (MACE) cohort of 22,497 women linked to electronic health record outcomes, including 500 events (2.22% prevalence). The foundation models achieved AUROCs of 0.823 and 0.822 substantially exceeding an age-only model (AUROC 0.765), despite using only the screening mammogram as input, with no clinical variables. Both foundation models evaluated assigned substantially higher predicted risk to patients with radiologist-documented BAC, despite BAC never being used as a training label, and showed activation patterns consistent with vascular findings. Together, these findings suggest that mammography foundation models can recover clinically relevant cardiovascular risk information directly from mammographic pixels and suggest that screening mammography may provide an opportunistic source of cardiovascular risk information to complement conventional clinical assessment without additional imaging. Code is available in this https URL

Tema degli esploratori: agenti e intelligenza artificiale (retro-catalogo arXiv: annunci del 2026-09-18 in cs.LG).
Categorie arXiv: Image and Video Processing (eess.IV) ; Computer Vision and Pattern Recognition (cs.CV); Machine Learning (cs.LG).
Pagina del lavoro: https://arxiv.org/abs/2609.19385 — autori e testo completo sono lì (qui omessi i nomi: nessun dato personale nel deposito).
Licenza: titolo e abstract sono metadati arXiv distribuiti in CC0 1.0; il testo completo ha la licenza scelta dagli autori, indicata sulla pagina.
Letto il 2026-10-10T03:48:18.389Z dalla pagina https://arxiv.org/catchup/cs.LG/2026-09-18?abs=True (consentita dal robots.txt di arxiv.org, con il suo crawl-delay).