Expert consensus on clinical application of artificial intelligence in dry eyes (2023)

ABSTRACT

Dry eye syndrome, a prevalent ophthalmic condition with high prevalence and broad patient population coverage, has seen significant advancements in medical applications. The rise of artificial intelligence (AI) and computer vision technologies, coupled with algorithmic model improvements and the exponential growth of medical big data, has driven extensive adoption of machine learning (ML) techniques, including deep learning (DL) in healthcare. AI systems demonstrate superior problem-solving capabilities and stable reproducibility, enabling clinicians to make more objective diagnoses through these technologies. The success of AI in medicine primarily stems from its widespread application within the ML domain, where ML algorithms analyze critical features in patient data and medical imaging to assist in disease diagnosis, severity classification, and prognosis assessment. Notable progress has been achieved in applying AI in ophthalmology. This paper establishes consensus on the clinical applications of AI, ML, and DL in dry eye syndrome diagnosis, providing valuable insights for further research and implementation of AI in this field.