Journal of Otolaryngology and Ophthalmology of Shandong University ›› 2026, Vol. 40 ›› Issue (3): 115-120.doi: 10.6040/j.issn.1673-3770.0.2025.334

• Review • Previous Articles    

Advances in the application of artificial intelligence to dry eye disease management

YANG Guanying1, LI Yuanbin2   

  1. 1. School of Clinical Medicine, Shandong Second Medical University, Weifang 261053, Shandong, China2. Department of Ophthalmology, Yantai Yuhuangding Hospital, Yantai 264000, Shandong, China
  • Published:2026-05-22

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Abstract: Artificial intelligence(AI)mimics human cognitive processes to facilitate data analysis and support decision-making. Dry eye disease(DED)is a common chronic disorder of the ocular surface, and conventional diagnosis and treatment rely on manual judgement, which is often subjective, unreliable, and inefficient. However, recent advances in image recognition, deep learning and multimodal data fusion have expanded the role of Al in medicine. This offers new approaches for the early screening, accurate diagnosis and personalised treatment of DED, as well as its long-term follow-up.This technology-focused review summarises recent advances in AI across all stages of DED clinical management. It analyses current technical limitations and implementation challenges, and highlights the value of Al in enhancing diagnostic objectivity, optimising individualised therapeutic strategies, and establishing intelligent monitoring systems. It also discusses future directions in Al-assisted DED management to guide the intelligent transformation of DED care and promote the practice of precision medicine.

Key words: Artificialintelligence, Dry eye disease, Deep learning, Machine learning, Multimodal data

CLC Number: 

  • R771.3
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