Abstract: Photorefraction technology determines the refractive status of children by analyzing images of light reflected from the retina. This method is suitable for younger children who have difficulty cooperating for extended periods, significantly enhancing the feasibility of early screening for myopia, hyperopia, astigmatism, and strabismus, making large-scale screenings possible. Photorefraction technology has evolved from film imaging to digitalization, miniaturization, and intelligence. In particular, the integration of artificial intelligence technology has significantly improved diagnostic accuracy and adaptability. Deep learning algorithms automatically analyze and extract features from eye images, enabling photorefractors to maintain high stability and accuracy in complex environments. The application of digital simulation technology also provides a scientific basis for further optimization of photorefraction technology, simulating imaging effects under different ocular conditions and providing strong support for improving device performance. With the commercialization of technology, various models of photorefractors have been developed, such as MTI, iScreen, PowerRefractor, Plusoptix, Spot, GoCheckKids, etc. These devices continue to improve in portability, ease of operation, and diagnostic accuracy, providing diverse options for screening refractive errors in children. Photorefraction technology is increasingly widely used in screening for refractive errors in children, with notable progress. Diagnostic accuracy and efficiency have been significantly improved, providing important technical support for early intervention and protection of global children's visual health. (Int Rev Ophthalmol, 2024, 48:  385-392)

Key words: photorefraction technology, refractive error, screening, artificial intelligence