小児の生物学的性別予測のためのAI搭載ECGの多施設検証

Donnchadh O'Sullivan¹, Joshua Mayourian², Scott Anjewierden³

¹Department of Pediatrics, Division of Pediatric Cardiology, Texas Children's Hospital and Baylor College of Medicine, Houston, TX, USA. donnchadhosull@gmail.com.

|February 26, 2026

Abstract:

Biological sex is closely linked to patterns embedded within the electrocardiogram (ECG) with essential health and disease implications. We report multicenter verification of an AI-enabled ECG model to predict biological sex across pediatric development. A previously published Mayo Clinic model confirmed puberty-linked AUROC gradient during external validation at Texas Children's Hospital (pre-puberty AUROC 0.64, peri-puberty AUROC 0.84, post-puberty AUROC 0.94). This phenomenon was replicated at Boston Children's Hospital. Saliency mapping revealed established sex-related electrophysiologic patterns.

キーワード:

人工知能心電図生物学的性別小児思春期心臓の電気生理学

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