Artificial intelligence in the diagnosis and management of refractive errors

Area of Science:

• Ophthalmology
• Medical Artificial Intelligence

Background:

• Refractive error is a primary cause of global visual impairment.
• Access to professional eye care for diagnosis and management is limited worldwide.

Purpose of the Study:

• To review the diverse applications of artificial intelligence (AI) in refractive error care.
• To explore AI's role in diagnosis, risk prediction, treatment, and emerging screening technologies.

Main Methods:

• Review of AI applications in axial length prediction from fundus images.
• Analysis of AI algorithms for myopia progression risk stratification.
• Examination of AI in vault size prediction for implantable lenses and orthokeratology.
• Assessment of AI in refractive surgery planning and outcomes.
• Inclusion of emerging digital technologies like telehealth and AI-integrated virtual reality for screening.

Main Results:

• AI demonstrates high accuracy in predicting axial length and stratifying myopia progression risk.
• AI models facilitate optimal lens fitting and vault size prediction for refractive treatments.
• AI shows promise in enhancing surgical planning and outcomes for refractive procedures.
• Digital health technologies integrated with AI offer new avenues for refractive error screening.

Conclusions:

• AI presents significant potential to revolutionize refractive error diagnosis and management.
• Widespread clinical implementation requires addressing challenges such as data limitations, standardization, and ethical considerations.