PLOS
open access
CC BY
Seeing the invisible: Reorienting cardiovascular risk prediction across the disease trajectory
Current risk equations miss many cardiovascular events in people classified as low risk. Prediction is simultaneously advancing on two axes: broadening predictors toward molecular omics, and expanding outcomes toward earlier subclinical atherosclerosis and later heart failure. In this Perspective,
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
- Development and evaluation of cardiovascular disease risk prediction models for patients with type 2 diabetes.#214215
- Acute Myocardial Infarction Clinical Cohort#1365680
- Health Improvements by Understanding the Determinants of Residual Risk in Coronary Artery Disease and New Targets for Prevention and Treatment#1171820
- AI-driven tools for the prediction of obesity-related vascular diseases: stakeholder perspectives and challenges#19958
- Risk prediction models for breast cancer integrating family history of breast cancer and prophylactic interventions#1104723
Record · ID 1416395
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
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
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive