儿童睡眠医学：为最年幼患者量身定制人工智能解决方案

文献信息

中文摘要

人工智能（AI）与儿童睡眠医学的相关性日益增强，该领域以复杂的生理信号、纵向行为数据、耗时的专家判读以及专科诊疗可及性不均为特征。由于睡眠生理、呼吸控制、症状表达和监测耐受性随发育而变化，儿科实践不能依赖源自成人的算法而不进行年龄特异性训练和验证。本综述重点介绍AI辅助阻塞性睡眠呼吸暂停筛查与严重程度评估、自动睡眠分期以及对活动记录仪和可穿戴设备信号进行更具信息性分析的当前证据。这些工具可能有助于减轻负担、支持家庭和纵向监测，并简化人工审核。

英文摘要

Artificial intelligence (AI) is increasingly relevant to pediatric sleep medicine, a field defined by complex physiologic signals, longitudinal behavioral data, time-intensive expert scoring, and uneven access to subspecialty care. Because sleep physiology, respiratory control, symptom expression, and monitoring tolerance change across development, pediatric practice cannot rely on adult-derived algorithms without age-specific training and validation. This review highlights the current evidence for AI-assisted obstructive sleep apnea screening and severity estimation, automated sleep staging, and more informative analysis of actigraphy and wearable signals. These tools may help reduce burden, support home and longitudinal monitoring, and streamline human review.