本文旨在深入探讨人工智能(artificial intelligence，AI)在眼科眼前节疾病诊断中的应用指南。由于眼前节疾病研究所涉及的图像较为复杂多变，AI既往在眼科主要应用于眼后段疾病，但随着AI技术的提升，尤其是机器学习和深度学习的发展，再加上眼前节电子影像数据的指数级增长，AI在角膜、结膜、晶状体和眼睑疾病领域的应用成为现实。中国医药教育协会眼科影像与智能医疗分会和国际转化医学会眼科专业委员会组织专家们结合近年来国内外AI在眼前节疾病诊断中的最新进展，包括在角膜、结膜、晶状体和眼睑疾病的应用，并分析当前面临的挑战和未来的发展方向，经过多轮讨论和修改，形成了该指南，旨在辅助眼科临床医生更好地应用AI进行眼前节疾病的诊断决策及临床研究。

This paper aims to delve deeply into the practical guidelines for the application of artificial intelligence(AI)in the diagnosis of anterior ocular diseases in ophthalmology. Given the complexities and variability inherent in the images associated with the research of anterior segment diseases, AI has traditionally found its principal application in the sphere of posterior segment diseases within ophthalmology. However, with the evolution and advancement of AI technologies, notably machine learning and deep learning, alongside an exponential surge in anterior segment electronic image data, the implementation of AI in the domain of corneal, conjunctival, lens, and eyelid disease is not only feasible but has become a reality. The Ophthalmic Imaging and Intelligent Medicine Branch of the Chinese Medical Education Association, in tandem with the Ophthalmology Professional Committee of the International Translational Medicine Association, have orchestrated a consortium of experts. These specialists have synthesized the most recent progressions, both nationally and internationally, in the application of AI in the diagnosis of anterior ocular diseases. This includes its use in corneal, conjunctival, lens, and eyelid diseases, and provides an analysis of the current challenges faced as well as the future directions of development. This guideline has been formulated through several iterations of thoughtful discussion and revisions. Its purpose is to empower clinical ophthalmologists with a reliable framework to facilitate the enhanced application of AI in diagnostic decision-making and clinical research for anterior ocular diseases.

国家自然科学基金项目(No.82160195); 江西省双千计划科技创新高端领军人才项目(No.jxsq2023201036); 江西省重大(重点)研发专项计划(No.20223BBH80014,20181BBG70004,20203BBG73059); 江西省杰出青年基金项目(No.20192BCBL23020)