人工智能应用于眼科专业人才培养的挑战与对策

Challenge and Strategy of Applying Artificial Intelligence in Ophthalmic Professionals Training

摘要:

在“人工智能+医学”蓬勃发展的态势下，作为人工智能应用先行者之一的眼科学，在疾病诊疗和人才培养方面都有广泛的应用和创新，积极推动从临床实践到专业人才培养的系统性转型，然而目前其将人工智能技术和理念的融入尚显不足。鉴于此，聚焦人工智能技术在眼科领域的创新应用，将文献分析和典型案例相结合，梳理总结人工智能在眼科疾病诊疗与专业人才培养中的实际成效，并进一步分析存在问题和对策。结果显示：人工智能在提升眼科临床诊断效率、优化学习路径和缩短专业人才培训周期方面展现出独特优势，特别是在智能影像分析、个性化学习路径设计及虚拟仿真训练中表现尤为突出；与此同时，人工智能技术的广泛应用仍受限于数据标准化不足、复杂眼病模型泛化能力不足以及伦理与隐私保护等问题。针对所面临的挑战，提出“人工智能+眼科”未来发展应聚焦标准化数据平台建设、跨学科协作与政策支持，以助力智能化、精准化的眼科人才培养与诊疗体系的构建。

Abstract:

With the vigorous development of "AI + medicine", ophthalmology, as one of the pioneers of artificial intelligence(AI) application, has a wide range of applications and innovation in disease diagnosis and treatment and talent training, actively promoting the systematic transformation from clinical practice to professional talent training. However, the current integration of AI technology and concept is still insufficient. In view of this, focusing on the innovative application of AI technology in ophthalmology, and combining systematic literature analysis and typical case analysis, this paper summarizes the actual achievements of AI in the diagnosis and treatment of ophthalmic diseases and the training of professional talents, and further analyzes the existing problems and countermeasures. The results show that AI has demonstrated unique advantages in improving the efficiency of ophthalmic clinical diagnosis, optimizing learning paths, and shortening the training cycle for professional talents, especially in intelligent image analysis, personalized learning path design, and virtual simulation training. However, the results also find that the widespread application of AI technology is still limited by issues such as insufficient data standardization, inadequate generalization ability of complex eye disease models, and ethical and privacy protection. In response to these challenges, future development of "AI + ophthalmology" should focus on the construction of standardized data platforms, interdisciplinary collaboration, as well as policies supporting to build an intelligent, precise ophthalmic professionals training, and ophthalmic diseases diagnosis and treatment system.