Wu Dawen, Huang Xi, Chen Liang, Hou Peixian, Liu Longqian, Yang Guoyuan
Department of Ophthalmology, West China Hospital, Sichuan University, Chengdu, China.
Laboratory of Optometry and Vision Sciences, West China Hospital, Sichuan University, Chengdu, China.
Exp Biol Med (Maywood). 2024 Nov 25;249:10320. doi: 10.3389/ebm.2024.10320. eCollection 2024.
Advancements in artificial intelligence (AI) are transforming strabismus management through improved screening, diagnosis, and surgical planning. Deep learning has notably enhanced diagnostic accuracy and optimized surgical outcomes. Despite these advancements, challenges such as the underrepresentation of diverse strabismus types and reliance on single-source data remain prevalent. Emphasizing the need for inclusive AI systems, future research should focus on expanding AI capabilities with large model technologies, integrating multimodal data to bridge existing gaps, and developing integrated management platforms to better accommodate diverse patient demographics and clinical scenarios.
人工智能(AI)的进步正在通过改进筛查、诊断和手术规划来改变斜视治疗。深度学习显著提高了诊断准确性并优化了手术效果。尽管取得了这些进展,但斜视类型代表性不足和依赖单一来源数据等挑战仍然普遍存在。强调需要包容性的人工智能系统,未来的研究应专注于利用大型模型技术扩展人工智能能力、整合多模态数据以弥合现有差距,以及开发综合管理平台以更好地适应不同的患者群体和临床情况。