NCBI PubMed Central
open access
Deep learning-derived biological age from preoperative chest radiographs predicts mortality following surgical and transcatheter procedures for structural heart disease beyond EuroSCORE II.
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
- Harnessing ECG Artificial Intelligence for Rapid Treatment and Accurate Identification of Structural Heart Disease#811572
- AI-ECG for Time-Resolved Prediction of HFrEF#1032867
- Hemodynamics and Myocardial Injury After Non-cardiac Surgery#884699
- Development of a Deep Learning Model for Opportunistic Screening of Osteoporosis using Chest Radiographs#1043978
- Artificial Intelligence - SARS-CoV-2 (COVID-19) Risk Evaluation#1164031
Record · ID 430854
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