Conceptio › Archive › ULRR
ULRR metadata only

Federated learning strategies for atrial fibrillation detection

Chorney, Wesley et al.
ULRR · Papers
Open Source ↗
3-good-health-and-well-beingatrial-fibrillationfederated-learningmachine-learning
Background: Different treatments may be required for paroxysmal versus non-paroxysmal atrial fibrillation. However, they may be difficult to distinguish on an electrocardiogram (ECG). Machine learning methods may aid in differentiating these conditions, yet current approaches either do not preserve
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 1180159
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