Lança, CarlaEmamian, Mohammad HassanGrzybowski, AndrzejGrzybowski, Andrzej2025-12-172025-12-172025-07Lança C, Emamian MH, Grzybowski A. Artificial Intelligence in refractive errors. In: Grzybowski A, editor. Artificial Intelligence in ophthalmology. Cham: Springer; 2025. p. 349-72.97830318375559783031837562http://hdl.handle.net/10400.21/22348Uncorrected refractive errors (URE) are a leading cause of visual impairment (VI) and blindness. Big data acquisition and computer technology analysis are expanding quickly. By combining traditional techniques with artificial intelligence (AI) based tools, several studies have shown great potential in the detection, prediction, and risk stratification of URE, especially myopia. Continued improvement of imaging techniques and methods to measure refraction, coupled with the application of new AI algorithms, may be the future of clinical practice and standard of care for the diagnosis and prognosis of refractive errors. This chapter reviews how AI can be applied to the field of URE and discusses challenges to implementation into clinical practice and future directions.engOphthalmologyArtificial IntelligenceUncorrected refractive errorsVisual impairmentMyopia detectionMyopia predictionAI-based risk stratificationAI algorithms in eye carebook part10.1007/978-3-031-83756-2_25