arXiv (All)
open access
Personalizable Models of Cardiac Elasticity with Physics-informed Symbolic Regression
Cardiac digital twins hold great promise for personalized medicine, but they currently depend on complex constitutive models of tissue mechanics that are often over-parameterized for the clinical context. To address this we introduce CHESRA (Cardiac Hyperelastic Evolutionary Symbolic Regression Algo
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
- Physics-Informed Symbolic Regression for Elasticity Modeling in Cardiac Digital Twins#179220
- Physical modeling applies to physiology, too#739335
- Cardiac Mechanics Modeling: Recent Developments and Current Challenges#485373
- Cardiac mechanics modeling: recent developments and current challenges#153131
- A text-book of medical physics : for the use of students and practitioners of medicine#1286269
Record · ID 1201907
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