Conceptio › Archive › arXiv (OAI Expanded)
arXiv (OAI Expanded) open access

CARDINAL Predicts Cardiovascular Risk From Non-contrast Cardiac CT

Gabriel, Roy et al.
arXiv (OAI Expanded) · Papers
Open Source ↗Direct PDF ↓
artificial-intelligencecomputer-vision-and-pattern-recognitionimage-and-video-processingmachine-learningrobotics
Cardiovascular risk prediction remains limited by incomplete clinical data and imaging biomarkers that reduce computed tomography (CT) to a small number of handcrafted features. We developed CARDINAL (Cardiovascular Assessment via Representation learning from Deep Imaging with Nested Anatomical Late
Conceptio Open Archive

Analyze & explore related research in Conceptio

Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.

This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗

Related documents

Record · ID 779613
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive