Rapid prediction of cardiac activation in the left ventricle with geometric deep learning: a step towards cardiac resynchronization therapy planning.

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Bibliographic Details
Title: Rapid prediction of cardiac activation in the left ventricle with geometric deep learning: a step towards cardiac resynchronization therapy planning.
Authors: Naghavi E; Dept. of Mechanical Engineering, Michigan State University, East Lansing, MI, US.; 3DT Holdings, LLC, San Diego, CA, US., Wang H; Dept. of Mechanical Engineering, Michigan State University, East Lansing, MI, US., Ziaei-Rad V; Dept. of Mechanical Engineering, Michigan State University, East Lansing, MI, US., Guccione J; 3DT Holdings, LLC, San Diego, CA, US.; California Medical Innovations Institute, San Diego, CA, US., Kassab G; 3DT Holdings, LLC, San Diego, CA, US.; California Medical Innovations Institute, San Diego, CA, US., Boddeti V; Dept. of Computer Science and Engineering, Michigan State University, East Lansing, MI, US., Baek S; Dept. of Mechanical Engineering, Michigan State University, East Lansing, MI, US., Lee LC; Dept. of Mechanical Engineering, Michigan State University, East Lansing, MI, US. lclee@egr.msu.edu.
Source: NPJ digital medicine [NPJ Digit Med] 2026 Feb 07; Vol. 9 (1). Date of Electronic Publication: 2026 Feb 07.
Publication Type: Journal Article
Journal Info: Publisher: Nature Publishing Group Country of Publication: England NLM ID: 101731738 Publication Model: Electronic Cited Medium: Internet ISSN: 2398-6352 (Electronic) Linking ISSN: 23986352 NLM ISO Abbreviation: NPJ Digit Med Subsets: PubMed not MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:2398-6352
DOI:10.1038/s41746-026-02399-7