Artificial Intelligence Enhanced Electrocardiogram Analysis for Age and Sex Classification in Youth.

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Bibliographic Details
Title: Artificial Intelligence Enhanced Electrocardiogram Analysis for Age and Sex Classification in Youth.
Authors: Zhang H; Department of Electrical and Computer Engineering, College of Engineering, University of Hawaii, Honolulu, HI, USA., Zaeri-Amirani M; Department of Electrical and Computer Engineering, College of Engineering, University of Hawaii, Honolulu, HI, USA., Abolfazli M; Department of Electrical and Computer Engineering, College of Engineering, University of Hawaii, Honolulu, HI, USA., Santhanam NP; Department of Electrical and Computer Engineering, College of Engineering, University of Hawaii, Honolulu, HI, USA., Zhang J; Department of Electrical and Computer Engineering, College of Engineering, University of Hawaii, Honolulu, HI, USA., Høst-Madsen A; Department of Electrical and Computer Engineering, College of Engineering, University of Hawaii, Honolulu, HI, USA., Kimata C; Patient Safety & Quality Services, Hawaii Pacific Health, Honolulu, HI, USA., Perry JC; Departments of Pediatrics and Bioengineering, University of California San Diego, San Diego, CA, USA., Bratincsak A; Department of Pediatrics, John A. Burns School of Medicine, University of Hawaii, Honolulu, HI, USA. andrasb@hphmg.org.; Hawaii Pacific Health Medical Group, Hawaii Pacific Health, 1319 Punahou St., Ste 950, Honolulu, HI, 96826, USA. andrasb@hphmg.org.
Source: Pediatric cardiology [Pediatr Cardiol] 2026 Feb 18. Date of Electronic Publication: 2026 Feb 18.
Publication Type: Journal Article
Journal Info: Publisher: Springer Verlag Country of Publication: United States NLM ID: 8003849 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1432-1971 (Electronic) Linking ISSN: 01720643 NLM ISO Abbreviation: Pediatr Cardiol Subsets: MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:1432-1971
DOI:10.1007/s00246-025-04118-7