[Artificial intelligence in pediatric ophthalmology: applications and perspectives].

内容摘要

Pediatric visual health is not only inextricably linked to an individual's lifelong cognitive development and quality of life, but also constitutes a major public health issue concerning the quality of the national population and the long-term development of the nation. However, the early identification and timely intervention of abnormal visual development in children are severely constrained by multiple factors: the shortage of specialized pediatric ophthalmologists, limited screening capacity in primary healthcare settings, and the highly insidious onset of most childhood ocular diseases. Against this backdrop, the widespread adoption of artificial intelligence (AI) technology has emerged as a core strategic pathway to improve screening coverage, ensure the standardization and consistency of diagnosis and treatment, and deliver inclusive pediatric eye health services. Nevertheless, the clinical application of AI in pediatric ophthalmology faces multiple challenges, including the scarcity of high-quality data on pediatric visual development, insufficient model robustness, limited generalization ability, the lack of multi-center clinical validation, and ethical and regulatory frameworks that lag behind technological innovation. This paper systematically summarizes the core bottlenecks and challenges confronting the promotion and application of AI technology in the field of pediatric ophthalmology, provides an in-depth analysis of its application prospects in childhood ocular disease screening, precision diagnosis and treatment, and full-cycle health management, and puts forward a strategic vision for building an open and collaborative national intelligent platform for pediatric eye health. This work aims to advance the deep integration of AI technology with standardized clinical practice in pediatric ophthalmology, and ultimately establish a new full-cycle, intelligent, and inclusive service system for pediatric eye health. 儿童视觉健康不仅关乎个体终身的认知发育与生活质量，更是关系国家人口素质与民族未来发展的重大公共卫生问题。然而，小儿眼科专业医师短缺、基层筛查能力有限、疾病隐匿性强等因素，严重制约了儿童异常视觉发育的早期识别与干预。在此背景下，推广人工智能（AI）技术是提升筛查覆盖率、保障诊疗同质化、实现儿童眼健康服务普惠化的发展方向。但是，AI在小儿眼科的应用面临高质量发育期数据稀缺、模型稳定性不足、泛化能力有限，多中心临床验证缺乏以及伦理监管体系滞后于技术创新等多重挑战。本文系统梳理了AI技术在小儿眼科领域推广应用面临的核心瓶颈与挑战，深入剖析其在儿童眼病筛查、精准诊疗及全周期健康管理中的应用前景，提出构建开放协同的国家级儿童眼健康智能平台的战略构想，旨在推动AI技术与小儿眼科专业诊疗的深度融合，最终实现覆盖全周期、智能化、普惠化的儿童眼健康服务新体系。.