Electrocardiography deep learning models to predict high-risk imaging features in patients with hypertrophic cardiomyopathy: Can it change clinical practice?
- PMID: 38365126
- DOI: 10.1016/j.hrthm.2024.02.023
Electrocardiography deep learning models to predict high-risk imaging features in patients with hypertrophic cardiomyopathy: Can it change clinical practice?
Conflict of interest statement
Disclosures Nassir Marrouche reports having received consulting fees from Biosense Webster, Boston Scientific, and AtriCure; being a speaker for Abbott, Biosense Webster, AtriCure, and Sanofi; and receiving research support from Abbott, Medtronic, Biosense Webster, Siemens, GE, Boston Scientific, Sanofi, and Samsung. He also reports having a family member as the CEO of Cardiac Designs, being the founder of Marrek, being named in a patent issued for magnetic resonance fibrosis imaging, and being a previous shareholder of Cardiac Designs. All other coauthors have no relevant conflict of interest.
Comment on
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Identification of high-risk imaging features in hypertrophic cardiomyopathy using electrocardiography: A deep-learning approach.Heart Rhythm. 2024 Aug;21(8):1390-1397. doi: 10.1016/j.hrthm.2024.01.031. Epub 2024 Jan 26. Heart Rhythm. 2024. PMID: 38280624 Free PMC article.
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