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Publicação
Artificial Intelligence in refractive errors
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Orientador(es)
Resumo(s)
Uncorrected 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.
Descrição
Palavras-chave
Ophthalmology Artificial Intelligence Uncorrected refractive errors Visual impairment Myopia detection Myopia prediction AI-based risk stratification AI algorithms in eye care
Contexto Educativo
Citação
Lança C, Emamian MH, Grzybowski A. Artificial Intelligence in refractive errors. In: Grzybowski A, editor. Artificial Intelligence in ophthalmology. Cham: Springer; 2025. p. 349-72.
Editora
Springer Nature Switzerland